Warning: Permanently added '3.84.167.128' (ED25519) to the list of known hosts. Running (timeout=18000): unbuffer mock --spec /var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms/R-CRAN-ubms.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1727860992.197419 -r /var/lib/copr-rpmbuild/results/configs/child.cfg INFO: mock.py version 5.6 starting (python version = 3.12.1, NVR = mock-5.6-1.fc39), args: /usr/libexec/mock/mock --spec /var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms/R-CRAN-ubms.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1727860992.197419 -r /var/lib/copr-rpmbuild/results/configs/child.cfg Start: init plugins INFO: tmpfs initialized INFO: selinux enabled INFO: chroot_scan: initialized INFO: compress_logs: initialized Finish: init plugins INFO: Signal handler active Start: run INFO: Start(/var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms/R-CRAN-ubms.spec) Config(fedora-rawhide-x86_64) Start: clean chroot Finish: clean chroot Mock Version: 5.6 INFO: Mock Version: 5.6 Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-rawhide-x86_64-1727860992.197419/root. INFO: calling preinit hooks INFO: enabled root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Package manager dnf5 detected and used (fallback) INFO: Buildroot is handled by package management from host and used with --installroot: rpm-4.19.1.1-1.fc39.x86_64 rpm-sequoia-1.6.0-1.fc39.x86_64 python3-dnf-4.21.1-1.fc39.noarch python3-dnf-plugins-core-4.9.0-1.fc39.noarch yum-4.21.1-1.fc39.noarch dnf5-5.1.17-2.fc39.x86_64 dnf5-plugins-5.1.17-2.fc39.x86_64 Start: installing minimal buildroot with dnf5 Updating and loading repositories: fedora 100% | 32.0 MiB/s | 21.9 MiB | 00m01s Copr repository 100% | 173.6 MiB/s | 12.5 MiB | 00m00s Repositories loaded. Package Arch Version Repository Size Installing group/module packages: bash x86_64 5.2.32-2.fc42 fedora 8.2 MiB bzip2 x86_64 1.0.8-19.fc41 fedora 95.7 KiB coreutils x86_64 9.5-10.fc42 fedora 5.7 MiB cpio x86_64 2.15-2.fc41 fedora 1.1 MiB diffutils x86_64 3.10-8.fc41 fedora 1.6 MiB fedora-release-common noarch 42-0.3 fedora 19.4 KiB findutils x86_64 1:4.10.0-4.fc41 fedora 1.8 MiB gawk x86_64 5.3.0-4.fc41 fedora 1.7 MiB glibc-minimal-langpack x86_64 2.40.9000-1.fc42 fedora 0.0 B grep x86_64 3.11-9.fc41 fedora 1.0 MiB gzip x86_64 1.13-2.fc41 fedora 389.0 KiB info x86_64 7.1.1-1.fc42 fedora 361.9 KiB patch x86_64 2.7.6-25.fc41 fedora 266.7 KiB redhat-rpm-config noarch 296-1.fc42 fedora 186.6 KiB rpm-build x86_64 4.19.94-1.fc42 fedora 194.3 KiB sed x86_64 4.9-3.fc41 fedora 861.5 KiB shadow-utils x86_64 2:4.16.0-4.fc42 fedora 4.1 MiB tar x86_64 2:1.35-4.fc41 fedora 2.9 MiB unzip x86_64 6.0-64.fc41 fedora 386.8 KiB util-linux x86_64 2.40.2-8.fc42 fedora 3.7 MiB which x86_64 2.21-42.fc41 fedora 80.2 KiB xz x86_64 1:5.6.2-2.fc41 fedora 1.2 MiB Installing dependencies: add-determinism x86_64 0.3.6-1.fc41 fedora 2.2 MiB alternatives x86_64 1.30-1.fc41 fedora 66.3 KiB ansible-srpm-macros noarch 1-16.fc41 fedora 35.7 KiB audit-libs x86_64 4.0.2-1.fc41 fedora 331.3 KiB authselect x86_64 1.5.0-7.fc41 fedora 153.5 KiB authselect-libs x86_64 1.5.0-7.fc41 fedora 818.3 KiB basesystem noarch 11-21.fc41 fedora 0.0 B binutils x86_64 2.43.1-1.fc42 fedora 27.5 MiB build-reproducibility-srpm-macros noarch 0.3.6-1.fc41 fedora 735.0 B bzip2-libs x86_64 1.0.8-19.fc41 fedora 80.7 KiB ca-certificates noarch 2024.2.69_v8.0.401-2.fc42 fedora 2.6 MiB coreutils-common x86_64 9.5-10.fc42 fedora 11.2 MiB cracklib x86_64 2.9.11-6.fc41 fedora 238.9 KiB crypto-policies noarch 20240828-1.git5f66e81.fc42 fedora 136.9 KiB curl x86_64 8.10.1-2.fc42 fedora 453.3 KiB cyrus-sasl-lib x86_64 2.1.28-27.fc41 fedora 2.3 MiB debugedit x86_64 5.0-17.fc41 fedora 199.3 KiB dwz x86_64 0.15-7.fc41 fedora 290.9 KiB ed x86_64 1.20.2-2.fc41 fedora 146.9 KiB efi-srpm-macros noarch 5-12.fc41 fedora 40.1 KiB elfutils x86_64 0.191-8.fc41 fedora 2.6 MiB elfutils-debuginfod-client x86_64 0.191-8.fc41 fedora 64.9 KiB elfutils-default-yama-scope noarch 0.191-8.fc41 fedora 1.8 KiB elfutils-libelf x86_64 0.191-8.fc41 fedora 1.2 MiB elfutils-libs x86_64 0.191-8.fc41 fedora 646.2 KiB fedora-gpg-keys noarch 42-0.2 fedora 126.4 KiB fedora-release noarch 42-0.3 fedora 0.0 B fedora-release-identity-basic noarch 42-0.3 fedora 694.0 B fedora-repos noarch 42-0.2 fedora 4.9 KiB fedora-repos-rawhide noarch 42-0.2 fedora 2.2 KiB file x86_64 5.45-7.fc41 fedora 103.5 KiB file-libs x86_64 5.45-7.fc41 fedora 9.9 MiB filesystem x86_64 3.18-29.fc42 fedora 106.0 B fonts-srpm-macros noarch 1:2.0.5-17.fc41 fedora 55.8 KiB forge-srpm-macros noarch 0.4.0-1.fc42 fedora 38.9 KiB fpc-srpm-macros noarch 1.3-13.fc41 fedora 144.0 B gdb-minimal x86_64 15.1-2.fc42 fedora 13.0 MiB gdbm x86_64 1:1.23-7.fc41 fedora 460.9 KiB gdbm-libs x86_64 1:1.23-7.fc41 fedora 121.9 KiB ghc-srpm-macros noarch 1.9.2-1.fc42 fedora 779.0 B glibc x86_64 2.40.9000-1.fc42 fedora 6.7 MiB glibc-common x86_64 2.40.9000-1.fc42 fedora 1.0 MiB glibc-gconv-extra x86_64 2.40.9000-1.fc42 fedora 8.1 MiB gmp x86_64 1:6.3.0-2.fc41 fedora 811.4 KiB gnat-srpm-macros noarch 6-6.fc41 fedora 1.0 KiB go-srpm-macros noarch 3.6.0-3.fc41 fedora 60.8 KiB jansson x86_64 2.13.1-10.fc41 fedora 88.3 KiB kernel-srpm-macros noarch 1.0-24.fc41 fedora 1.9 KiB keyutils-libs x86_64 1.6.3-4.fc41 fedora 54.4 KiB krb5-libs x86_64 1.21.3-2.fc41 fedora 2.3 MiB libacl x86_64 2.3.2-2.fc41 fedora 40.0 KiB libarchive x86_64 3.7.6-1.fc42 fedora 934.8 KiB libattr x86_64 2.5.2-4.fc41 fedora 28.5 KiB libblkid x86_64 2.40.2-8.fc42 fedora 262.5 KiB libbrotli x86_64 1.1.0-5.fc41 fedora 837.6 KiB libcap x86_64 2.70-4.fc41 fedora 220.2 KiB libcap-ng x86_64 0.8.5-3.fc41 fedora 69.2 KiB libcom_err x86_64 1.47.1-3.fc41 fedora 67.2 KiB libcurl x86_64 8.10.1-2.fc42 fedora 838.4 KiB libeconf x86_64 0.6.2-3.fc41 fedora 58.0 KiB libevent x86_64 2.1.12-14.fc41 fedora 895.7 KiB libfdisk x86_64 2.40.2-8.fc42 fedora 362.9 KiB libffi x86_64 3.4.6-3.fc42 fedora 86.4 KiB libgcc x86_64 14.2.1-4.fc42 fedora 274.6 KiB libgomp x86_64 14.2.1-4.fc42 fedora 523.8 KiB libidn2 x86_64 2.3.7-2.fc41 fedora 329.1 KiB libmount x86_64 2.40.2-8.fc42 fedora 355.8 KiB libnghttp2 x86_64 1.63.0-1.fc42 fedora 170.1 KiB libnsl2 x86_64 2.0.1-2.fc41 fedora 57.9 KiB libpkgconf x86_64 2.3.0-1.fc42 fedora 78.2 KiB libpsl x86_64 0.21.5-4.fc41 fedora 80.5 KiB libpwquality x86_64 1.4.5-11.fc41 fedora 417.8 KiB libselinux x86_64 3.7-6.fc42 fedora 181.1 KiB libsemanage x86_64 3.7-3.fc42 fedora 298.0 KiB libsepol x86_64 3.7-3.fc42 fedora 818.0 KiB libsmartcols x86_64 2.40.2-8.fc42 fedora 180.4 KiB libssh x86_64 0.11.1-1.fc42 fedora 569.6 KiB libssh-config noarch 0.11.1-1.fc42 fedora 277.0 B libstdc++ x86_64 14.2.1-4.fc42 fedora 2.8 MiB libtasn1 x86_64 4.19.0-9.fc41 fedora 175.7 KiB libtirpc x86_64 1.3.5-0.fc41 fedora 202.7 KiB libtool-ltdl x86_64 2.4.7-12.fc41 fedora 66.2 KiB libunistring x86_64 1.1-8.fc41 fedora 1.7 MiB libuuid x86_64 2.40.2-8.fc42 fedora 41.4 KiB libverto x86_64 0.3.2-9.fc41 fedora 29.5 KiB libxcrypt x86_64 4.4.36-7.fc41 fedora 266.8 KiB libxml2 x86_64 2.12.8-2.fc41 fedora 1.7 MiB libzstd x86_64 1.5.6-2.fc41 fedora 795.9 KiB lua-libs x86_64 5.4.6-6.fc41 fedora 285.0 KiB lua-srpm-macros noarch 1-14.fc41 fedora 1.3 KiB lz4-libs x86_64 1.10.0-1.fc41 fedora 145.5 KiB mpfr x86_64 4.2.1-5.fc41 fedora 832.1 KiB ncurses-base noarch 6.5-2.20240629.fc41 fedora 326.3 KiB ncurses-libs x86_64 6.5-2.20240629.fc41 fedora 975.2 KiB ocaml-srpm-macros noarch 10-3.fc41 fedora 1.9 KiB openblas-srpm-macros noarch 2-18.fc41 fedora 112.0 B openldap x86_64 2.6.8-5.fc41 fedora 644.2 KiB openssl-libs x86_64 1:3.2.2-8.fc42 fedora 7.8 MiB p11-kit x86_64 0.25.5-3.fc41 fedora 2.2 MiB p11-kit-trust x86_64 0.25.5-3.fc41 fedora 391.4 KiB package-notes-srpm-macros noarch 0.5-12.fc41 fedora 1.6 KiB pam x86_64 1.6.1-6.fc42 fedora 1.8 MiB pam-libs x86_64 1.6.1-6.fc42 fedora 139.0 KiB pcre2 x86_64 10.44-1.fc41.1 fedora 653.5 KiB pcre2-syntax noarch 10.44-1.fc41.1 fedora 251.6 KiB perl-srpm-macros noarch 1-56.fc41 fedora 861.0 B pkgconf x86_64 2.3.0-1.fc42 fedora 88.6 KiB pkgconf-m4 noarch 2.3.0-1.fc42 fedora 14.4 KiB pkgconf-pkg-config x86_64 2.3.0-1.fc42 fedora 989.0 B popt x86_64 1.19-7.fc41 fedora 136.9 KiB publicsuffix-list-dafsa noarch 20240107-4.fc41 fedora 67.5 KiB pyproject-srpm-macros noarch 1.15.0-1.fc42 fedora 1.9 KiB python-srpm-macros noarch 3.13-3.fc41 fedora 51.0 KiB qt5-srpm-macros noarch 5.15.15-1.fc42 fedora 500.0 B qt6-srpm-macros noarch 6.7.2-3.fc41 fedora 456.0 B readline x86_64 8.2-11.fc42 fedora 493.1 KiB rpm x86_64 4.19.94-1.fc42 fedora 3.1 MiB rpm-build-libs x86_64 4.19.94-1.fc42 fedora 206.7 KiB rpm-libs x86_64 4.19.94-1.fc42 fedora 722.1 KiB rpm-sequoia x86_64 1.7.0-2.fc41 fedora 2.4 MiB rust-srpm-macros noarch 26.3-3.fc42 fedora 4.8 KiB setup noarch 2.15.0-5.fc41 fedora 720.7 KiB sqlite-libs x86_64 3.46.0-4.fc41 fedora 1.4 MiB systemd-libs x86_64 256.5-1.fc42 fedora 2.0 MiB util-linux-core x86_64 2.40.2-8.fc42 fedora 1.5 MiB xxhash-libs x86_64 0.8.2-3.fc41 fedora 88.5 KiB xz-libs x86_64 1:5.6.2-2.fc41 fedora 214.4 KiB zig-srpm-macros noarch 1-3.fc41 fedora 1.1 KiB zip x86_64 3.0-41.fc41 fedora 703.2 KiB zlib-ng-compat x86_64 2.1.7-3.fc42 fedora 138.0 KiB zstd x86_64 1.5.6-2.fc41 fedora 1.7 MiB Installing groups: Buildsystem building group Transaction Summary: Installing: 153 packages Total size of inbound packages is 53 MiB. Need to download 53 MiB. After this operation 180 MiB will be used (install 180 MiB, remove 0 B). [ 1/153] bzip2-0:1.0.8-19.fc41.x86_64 100% | 3.2 MiB/s | 52.5 KiB | 00m00s [ 2/153] coreutils-0:9.5-10.fc42.x86_6 100% | 52.7 MiB/s | 1.1 MiB | 00m00s [ 3/153] cpio-0:2.15-2.fc41.x86_64 100% | 40.7 MiB/s | 291.8 KiB | 00m00s [ 4/153] bash-0:5.2.32-2.fc42.x86_64 100% | 66.9 MiB/s | 1.8 MiB | 00m00s [ 5/153] diffutils-0:3.10-8.fc41.x86_6 100% | 66.0 MiB/s | 405.4 KiB | 00m00s [ 6/153] fedora-release-common-0:42-0. 100% | 11.2 MiB/s | 23.0 KiB | 00m00s [ 7/153] glibc-minimal-langpack-0:2.40 100% | 59.0 MiB/s | 120.9 KiB | 00m00s [ 8/153] grep-0:3.11-9.fc41.x86_64 100% | 73.2 MiB/s | 299.8 KiB | 00m00s [ 9/153] findutils-1:4.10.0-4.fc41.x86 100% | 107.1 MiB/s | 548.6 KiB | 00m00s [ 10/153] gzip-0:1.13-2.fc41.x86_64 100% | 55.4 MiB/s | 170.2 KiB | 00m00s [ 11/153] info-0:7.1.1-1.fc42.x86_64 100% | 59.5 MiB/s | 182.8 KiB | 00m00s [ 12/153] patch-0:2.7.6-25.fc41.x86_64 100% | 63.9 MiB/s | 131.0 KiB | 00m00s [ 13/153] redhat-rpm-config-0:296-1.fc4 100% | 40.3 MiB/s | 82.4 KiB | 00m00s [ 14/153] rpm-build-0:4.19.94-1.fc42.x8 100% | 40.6 MiB/s | 83.1 KiB | 00m00s [ 15/153] sed-0:4.9-3.fc41.x86_64 100% | 103.4 MiB/s | 317.7 KiB | 00m00s [ 16/153] tar-2:1.35-4.fc41.x86_64 100% | 210.1 MiB/s | 860.7 KiB | 00m00s [ 17/153] shadow-utils-2:4.16.0-4.fc42. 100% | 164.5 MiB/s | 1.3 MiB | 00m00s [ 18/153] unzip-0:6.0-64.fc41.x86_64 100% | 30.1 MiB/s | 184.9 KiB | 00m00s [ 19/153] which-0:2.21-42.fc41.x86_64 100% | 13.5 MiB/s | 41.6 KiB | 00m00s [ 20/153] xz-1:5.6.2-2.fc41.x86_64 100% | 115.1 MiB/s | 471.5 KiB | 00m00s [ 21/153] gawk-0:5.3.0-4.fc41.x86_64 100% | 178.5 MiB/s | 1.1 MiB | 00m00s [ 22/153] util-linux-0:2.40.2-8.fc42.x8 100% | 166.1 MiB/s | 1.2 MiB | 00m00s [ 23/153] filesystem-0:3.18-29.fc42.x86 100% | 181.1 MiB/s | 1.1 MiB | 00m00s [ 24/153] ncurses-libs-0:6.5-2.20240629 100% | 108.7 MiB/s | 334.0 KiB | 00m00s [ 25/153] bzip2-libs-0:1.0.8-19.fc41.x8 100% | 13.4 MiB/s | 41.1 KiB | 00m00s [ 26/153] glibc-0:2.40.9000-1.fc42.x86_ 100% | 160.3 MiB/s | 2.2 MiB | 00m00s [ 27/153] coreutils-common-0:9.5-10.fc4 100% | 192.9 MiB/s | 2.1 MiB | 00m00s [ 28/153] gmp-1:6.3.0-2.fc41.x86_64 100% | 34.5 MiB/s | 318.0 KiB | 00m00s [ 29/153] libacl-0:2.3.2-2.fc41.x86_64 100% | 12.0 MiB/s | 24.5 KiB | 00m00s [ 30/153] libattr-0:2.5.2-4.fc41.x86_64 100% | 17.7 MiB/s | 18.2 KiB | 00m00s [ 31/153] libcap-0:2.70-4.fc41.x86_64 100% | 42.3 MiB/s | 86.7 KiB | 00m00s [ 32/153] libselinux-0:3.7-6.fc42.x86_6 100% | 43.2 MiB/s | 88.6 KiB | 00m00s [ 33/153] fedora-repos-0:42-0.2.noarch 100% | 9.0 MiB/s | 9.2 KiB | 00m00s [ 34/153] systemd-libs-0:256.5-1.fc42.x 100% | 178.3 MiB/s | 730.4 KiB | 00m00s [ 35/153] openssl-libs-1:3.2.2-8.fc42.x 100% | 231.0 MiB/s | 2.3 MiB | 00m00s [ 36/153] glibc-common-0:2.40.9000-1.fc 100% | 44.4 MiB/s | 409.4 KiB | 00m00s [ 37/153] pcre2-0:10.44-1.fc41.1.x86_64 100% | 39.6 MiB/s | 243.1 KiB | 00m00s [ 38/153] ed-0:1.20.2-2.fc41.x86_64 100% | 39.9 MiB/s | 81.8 KiB | 00m00s [ 39/153] ansible-srpm-macros-0:1-16.fc 100% | 10.1 MiB/s | 20.8 KiB | 00m00s [ 40/153] build-reproducibility-srpm-ma 100% | 5.2 MiB/s | 10.6 KiB | 00m00s [ 41/153] efi-srpm-macros-0:5-12.fc41.n 100% | 10.9 MiB/s | 22.4 KiB | 00m00s [ 42/153] dwz-0:0.15-7.fc41.x86_64 100% | 67.4 MiB/s | 138.0 KiB | 00m00s [ 43/153] file-0:5.45-7.fc41.x86_64 100% | 24.0 MiB/s | 49.1 KiB | 00m00s [ 44/153] fonts-srpm-macros-1:2.0.5-17. 100% | 13.2 MiB/s | 27.0 KiB | 00m00s [ 45/153] fpc-srpm-macros-0:1.3-13.fc41 100% | 7.8 MiB/s | 8.0 KiB | 00m00s [ 46/153] forge-srpm-macros-0:0.4.0-1.f 100% | 9.6 MiB/s | 19.8 KiB | 00m00s [ 47/153] ghc-srpm-macros-0:1.9.2-1.fc4 100% | 8.9 MiB/s | 9.1 KiB | 00m00s [ 48/153] gnat-srpm-macros-0:6-6.fc41.n 100% | 8.7 MiB/s | 9.0 KiB | 00m00s [ 49/153] kernel-srpm-macros-0:1.0-24.f 100% | 9.6 MiB/s | 9.9 KiB | 00m00s [ 50/153] lua-srpm-macros-0:1-14.fc41.n 100% | 8.7 MiB/s | 8.9 KiB | 00m00s [ 51/153] go-srpm-macros-0:3.6.0-3.fc41 100% | 9.1 MiB/s | 28.0 KiB | 00m00s [ 52/153] openblas-srpm-macros-0:2-18.f 100% | 7.5 MiB/s | 7.7 KiB | 00m00s [ 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| 7.0 MiB/s | 14.3 KiB | 00m00s [130/153] libpkgconf-0:2.3.0-1.fc42.x86 100% | 12.5 MiB/s | 38.5 KiB | 00m00s [131/153] gdbm-1:1.23-7.fc41.x86_64 100% | 37.1 MiB/s | 151.8 KiB | 00m00s [132/153] libffi-0:3.4.6-3.fc42.x86_64 100% | 13.0 MiB/s | 40.0 KiB | 00m00s [133/153] p11-kit-0:0.25.5-3.fc41.x86_6 100% | 159.8 MiB/s | 490.9 KiB | 00m00s [134/153] libtasn1-0:4.19.0-9.fc41.x86_ 100% | 24.2 MiB/s | 74.2 KiB | 00m00s [135/153] binutils-0:2.43.1-1.fc42.x86_ 100% | 268.8 MiB/s | 6.5 MiB | 00m00s [136/153] p11-kit-trust-0:0.25.5-3.fc41 100% | 18.4 MiB/s | 132.1 KiB | 00m00s [137/153] fedora-release-0:42-0.3.noarc 100% | 2.0 MiB/s | 12.2 KiB | 00m00s [138/153] xxhash-libs-0:0.8.2-3.fc41.x8 100% | 18.1 MiB/s | 37.1 KiB | 00m00s [139/153] fedora-release-identity-basic 100% | 6.4 MiB/s | 13.0 KiB | 00m00s [140/153] libcurl-0:8.10.1-2.fc42.x86_6 100% | 120.9 MiB/s | 371.3 KiB | 00m00s [141/153] libbrotli-0:1.1.0-5.fc41.x86_ 100% | 83.1 MiB/s | 340.5 KiB | 00m00s [142/153] 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-------------------------------------------------------------------------------- [153/153] Total 100% | 190.0 MiB/s | 53.2 MiB | 00m00s Running transaction Importing PGP key 0x105EF944: Userid : "Fedora (42) " Fingerprint: B0F4950458F69E1150C6C5EDC8AC4916105EF944 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-42-primary The key was successfully imported. Importing PGP key 0x105EF944: Userid : "Fedora (42) " Fingerprint: B0F4950458F69E1150C6C5EDC8AC4916105EF944 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-42-primary The key was successfully imported. Importing PGP key 0xE99D6AD1: Userid : "Fedora (41) " Fingerprint: 466CF2D8B60BC3057AA9453ED0622462E99D6AD1 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-41-primary The key was successfully imported. Importing PGP key 0x31645531: Userid : "Fedora (43) " Fingerprint: C6E7F081CF80E13146676E88829B606631645531 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-43-primary The key was successfully imported. [ 1/155] Verify package files 100% | 772.0 B/s | 153.0 B | 00m00s >>> Running pre-transaction scriptlet: filesystem-0:3.18-29.fc42.x86_64 >>> Stop pre-transaction scriptlet: filesystem-0:3.18-29.fc42.x86_64 [ 2/155] Prepare transaction 100% | 3.6 KiB/s | 153.0 B | 00m00s [ 3/155] Installing libgcc-0:14.2.1-4. 100% | 269.8 MiB/s | 276.3 KiB | 00m00s >>> Running post-install scriptlet: libgcc-0:14.2.1-4.fc42.x86_64 >>> Stop post-install scriptlet: libgcc-0:14.2.1-4.fc42.x86_64 [ 4/155] Installing fedora-release-ide 100% | 0.0 B/s | 952.0 B | 00m00s [ 5/155] Installing fedora-repos-rawhi 100% | 2.4 MiB/s | 2.4 KiB | 00m00s [ 6/155] Installing fedora-gpg-keys-0: 100% | 56.1 MiB/s | 172.2 KiB | 00m00s [ 7/155] Installing fedora-repos-0:42- 100% | 0.0 B/s | 5.7 KiB | 00m00s [ 8/155] Installing fedora-release-com 100% | 23.1 MiB/s | 23.7 KiB | 00m00s [ 9/155] Installing fedora-release-0:4 100% | 0.0 B/s | 124.0 B | 00m00s [ 10/155] Installing setup-0:2.15.0-5.f 100% | 59.1 MiB/s | 726.1 KiB | 00m00s >>> Running post-install scriptlet: setup-0:2.15.0-5.fc41.noarch >>> Stop post-install scriptlet: setup-0:2.15.0-5.fc41.noarch [ 11/155] Installing filesystem-0:3.18- 100% | 3.2 MiB/s | 212.6 KiB | 00m00s [ 12/155] Installing basesystem-0:11-21 100% | 0.0 B/s | 124.0 B | 00m00s [ 13/155] Installing libssh-config-0:0. 100% | 0.0 B/s | 816.0 B | 00m00s [ 14/155] Installing publicsuffix-list- 100% | 0.0 B/s | 68.3 KiB | 00m00s [ 15/155] Installing pkgconf-m4-0:2.3.0 100% | 0.0 B/s | 14.8 KiB | 00m00s [ 16/155] Installing pcre2-syntax-0:10. 100% | 248.1 MiB/s | 254.1 KiB | 00m00s [ 17/155] Installing ncurses-base-0:6.5 100% | 85.9 MiB/s | 351.7 KiB | 00m00s [ 18/155] Installing glibc-minimal-lang 100% | 0.0 B/s | 124.0 B | 00m00s [ 19/155] Installing ncurses-libs-0:6.5 100% | 191.8 MiB/s | 981.8 KiB | 00m00s >>> Running pre-install scriptlet: glibc-0:2.40.9000-1.fc42.x86_64 >>> Stop pre-install scriptlet: glibc-0:2.40.9000-1.fc42.x86_64 [ 20/155] Installing glibc-0:2.40.9000- 100% | 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00m00s [ 96/155] Installing pkgconf-0:2.3.0-1. 100% | 89.0 MiB/s | 91.1 KiB | 00m00s [ 97/155] Installing pkgconf-pkg-config 100% | 0.0 B/s | 1.8 KiB | 00m00s [ 98/155] Installing xxhash-libs-0:0.8. 100% | 87.8 MiB/s | 89.9 KiB | 00m00s [ 99/155] Installing libbrotli-0:1.1.0- 100% | 273.4 MiB/s | 839.9 KiB | 00m00s [100/155] Installing libnghttp2-0:1.63. 100% | 167.2 MiB/s | 171.2 KiB | 00m00s [101/155] Installing libtool-ltdl-0:2.4 100% | 65.7 MiB/s | 67.3 KiB | 00m00s [102/155] Installing rust-srpm-macros-0 100% | 0.0 B/s | 5.6 KiB | 00m00s [103/155] Installing qt6-srpm-macros-0: 100% | 0.0 B/s | 732.0 B | 00m00s [104/155] Installing qt5-srpm-macros-0: 100% | 0.0 B/s | 776.0 B | 00m00s [105/155] Installing perl-srpm-macros-0 100% | 0.0 B/s | 1.1 KiB | 00m00s [106/155] Installing package-notes-srpm 100% | 0.0 B/s | 2.0 KiB | 00m00s [107/155] Installing openblas-srpm-macr 100% | 0.0 B/s | 392.0 B | 00m00s [108/155] Installing ocaml-srpm-macros- 100% | 0.0 B/s | 2.2 KiB | 00m00s 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[130/155] Installing libevent-0:2.1.12- 100% | 292.8 MiB/s | 899.5 KiB | 00m00s [131/155] Installing openldap-0:2.6.8-5 100% | 210.9 MiB/s | 648.0 KiB | 00m00s [132/155] Installing libcurl-0:8.10.1-2 100% | 273.3 MiB/s | 839.5 KiB | 00m00s [133/155] Installing elfutils-libs-0:0. 100% | 210.9 MiB/s | 648.0 KiB | 00m00s [134/155] Installing elfutils-debuginfo 100% | 65.3 MiB/s | 66.9 KiB | 00m00s [135/155] Installing elfutils-0:0.191-8 100% | 365.7 MiB/s | 2.6 MiB | 00m00s [136/155] Installing binutils-0:2.43.1- 100% | 377.2 MiB/s | 27.5 MiB | 00m00s >>> Running post-install scriptlet: binutils-0:2.43.1-1.fc42.x86_64 >>> Stop post-install scriptlet: binutils-0:2.43.1-1.fc42.x86_64 [137/155] Installing gdb-minimal-0:15.1 100% | 393.8 MiB/s | 13.0 MiB | 00m00s [138/155] Installing debugedit-0:5.0-17 100% | 197.3 MiB/s | 202.0 KiB | 00m00s [139/155] Installing rpm-build-libs-0:4 100% | 202.6 MiB/s | 207.5 KiB | 00m00s [140/155] Installing curl-0:8.10.1-2.fc 100% | 44.5 MiB/s | 455.8 KiB | 00m00s >>> Running pre-install scriptlet: rpm-0:4.19.94-1.fc42.x86_64 >>> Stop pre-install scriptlet: rpm-0:4.19.94-1.fc42.x86_64 [141/155] Installing rpm-0:4.19.94-1.fc 100% | 167.1 MiB/s | 2.5 MiB | 00m00s [142/155] Installing efi-srpm-macros-0: 100% | 0.0 B/s | 41.2 KiB | 00m00s [143/155] Installing lua-srpm-macros-0: 100% | 0.0 B/s | 1.9 KiB | 00m00s [144/155] Installing zig-srpm-macros-0: 100% | 0.0 B/s | 1.7 KiB | 00m00s [145/155] Installing fonts-srpm-macros- 100% | 55.7 MiB/s | 57.0 KiB | 00m00s [146/155] Installing forge-srpm-macros- 100% | 39.3 MiB/s | 40.3 KiB | 00m00s [147/155] Installing go-srpm-macros-0:3 100% | 60.5 MiB/s | 62.0 KiB | 00m00s [148/155] Installing python-srpm-macros 100% | 50.9 MiB/s | 52.2 KiB | 00m00s [149/155] Installing redhat-rpm-config- 100% | 94.4 MiB/s | 193.2 KiB | 00m00s [150/155] Installing rpm-build-0:4.19.9 100% | 99.1 MiB/s | 202.9 KiB | 00m00s [151/155] Installing pyproject-srpm-mac 100% | 1.2 MiB/s | 2.5 KiB | 00m00s [152/155] Installing util-linux-0:2.40. 100% | 176.9 MiB/s | 3.7 MiB | 00m00s >>> Running post-install scriptlet: util-linux-0:2.40.2-8.fc42.x86_64 >>> Stop post-install scriptlet: util-linux-0:2.40.2-8.fc42.x86_64 [153/155] Installing authselect-0:1.5.0 100% | 77.1 MiB/s | 157.9 KiB | 00m00s [154/155] Installing which-0:2.21-42.fc 100% | 80.5 MiB/s | 82.4 KiB | 00m00s [155/155] Installing info-0:7.1.1-1.fc4 100% | 224.0 KiB/s | 362.3 KiB | 00m02s >>> Running post-transaction scriptlet: filesystem-0:3.18-29.fc42.x86_64 >>> Stop post-transaction scriptlet: filesystem-0:3.18-29.fc42.x86_64 >>> Running post-transaction scriptlet: ca-certificates-0:2024.2.69_v8.0.401-2.f >>> Stop post-transaction scriptlet: ca-certificates-0:2024.2.69_v8.0.401-2.fc42 >>> Running post-transaction scriptlet: authselect-libs-0:1.5.0-7.fc41.x86_64 >>> Stop post-transaction scriptlet: authselect-libs-0:1.5.0-7.fc41.x86_64 >>> Running post-transaction scriptlet: rpm-0:4.19.94-1.fc42.x86_64 >>> Stop post-transaction scriptlet: rpm-0:4.19.94-1.fc42.x86_64 >>> Running trigger-install scriptlet: glibc-common-0:2.40.9000-1.fc42.x86_64 >>> Stop trigger-install scriptlet: glibc-common-0:2.40.9000-1.fc42.x86_64 >>> Running trigger-install scriptlet: info-0:7.1.1-1.fc42.x86_64 >>> Stop trigger-install scriptlet: info-0:7.1.1-1.fc42.x86_64 Finish: installing minimal buildroot with dnf5 Start: creating root cache Finish: creating root cache Finish: chroot init INFO: Installed packages: INFO: add-determinism-0.3.6-1.fc41.x86_64 alternatives-1.30-1.fc41.x86_64 ansible-srpm-macros-1-16.fc41.noarch audit-libs-4.0.2-1.fc41.x86_64 authselect-1.5.0-7.fc41.x86_64 authselect-libs-1.5.0-7.fc41.x86_64 basesystem-11-21.fc41.noarch bash-5.2.32-2.fc42.x86_64 binutils-2.43.1-1.fc42.x86_64 build-reproducibility-srpm-macros-0.3.6-1.fc41.noarch bzip2-1.0.8-19.fc41.x86_64 bzip2-libs-1.0.8-19.fc41.x86_64 ca-certificates-2024.2.69_v8.0.401-2.fc42.noarch coreutils-9.5-10.fc42.x86_64 coreutils-common-9.5-10.fc42.x86_64 cpio-2.15-2.fc41.x86_64 cracklib-2.9.11-6.fc41.x86_64 crypto-policies-20240828-1.git5f66e81.fc42.noarch curl-8.10.1-2.fc42.x86_64 cyrus-sasl-lib-2.1.28-27.fc41.x86_64 debugedit-5.0-17.fc41.x86_64 diffutils-3.10-8.fc41.x86_64 dwz-0.15-7.fc41.x86_64 ed-1.20.2-2.fc41.x86_64 efi-srpm-macros-5-12.fc41.noarch elfutils-0.191-8.fc41.x86_64 elfutils-debuginfod-client-0.191-8.fc41.x86_64 elfutils-default-yama-scope-0.191-8.fc41.noarch elfutils-libelf-0.191-8.fc41.x86_64 elfutils-libs-0.191-8.fc41.x86_64 fedora-gpg-keys-42-0.2.noarch fedora-release-42-0.3.noarch fedora-release-common-42-0.3.noarch fedora-release-identity-basic-42-0.3.noarch fedora-repos-42-0.2.noarch fedora-repos-rawhide-42-0.2.noarch file-5.45-7.fc41.x86_64 file-libs-5.45-7.fc41.x86_64 filesystem-3.18-29.fc42.x86_64 findutils-4.10.0-4.fc41.x86_64 fonts-srpm-macros-2.0.5-17.fc41.noarch forge-srpm-macros-0.4.0-1.fc42.noarch fpc-srpm-macros-1.3-13.fc41.noarch gawk-5.3.0-4.fc41.x86_64 gdb-minimal-15.1-2.fc42.x86_64 gdbm-1.23-7.fc41.x86_64 gdbm-libs-1.23-7.fc41.x86_64 ghc-srpm-macros-1.9.2-1.fc42.noarch glibc-2.40.9000-1.fc42.x86_64 glibc-common-2.40.9000-1.fc42.x86_64 glibc-gconv-extra-2.40.9000-1.fc42.x86_64 glibc-minimal-langpack-2.40.9000-1.fc42.x86_64 gmp-6.3.0-2.fc41.x86_64 gnat-srpm-macros-6-6.fc41.noarch go-srpm-macros-3.6.0-3.fc41.noarch gpg-pubkey-105ef944-65ca83d1 gpg-pubkey-31645531-66b6dccf gpg-pubkey-e99d6ad1-64d2612c grep-3.11-9.fc41.x86_64 gzip-1.13-2.fc41.x86_64 info-7.1.1-1.fc42.x86_64 jansson-2.13.1-10.fc41.x86_64 kernel-srpm-macros-1.0-24.fc41.noarch keyutils-libs-1.6.3-4.fc41.x86_64 krb5-libs-1.21.3-2.fc41.x86_64 libacl-2.3.2-2.fc41.x86_64 libarchive-3.7.6-1.fc42.x86_64 libattr-2.5.2-4.fc41.x86_64 libblkid-2.40.2-8.fc42.x86_64 libbrotli-1.1.0-5.fc41.x86_64 libcap-2.70-4.fc41.x86_64 libcap-ng-0.8.5-3.fc41.x86_64 libcom_err-1.47.1-3.fc41.x86_64 libcurl-8.10.1-2.fc42.x86_64 libeconf-0.6.2-3.fc41.x86_64 libevent-2.1.12-14.fc41.x86_64 libfdisk-2.40.2-8.fc42.x86_64 libffi-3.4.6-3.fc42.x86_64 libgcc-14.2.1-4.fc42.x86_64 libgomp-14.2.1-4.fc42.x86_64 libidn2-2.3.7-2.fc41.x86_64 libmount-2.40.2-8.fc42.x86_64 libnghttp2-1.63.0-1.fc42.x86_64 libnsl2-2.0.1-2.fc41.x86_64 libpkgconf-2.3.0-1.fc42.x86_64 libpsl-0.21.5-4.fc41.x86_64 libpwquality-1.4.5-11.fc41.x86_64 libselinux-3.7-6.fc42.x86_64 libsemanage-3.7-3.fc42.x86_64 libsepol-3.7-3.fc42.x86_64 libsmartcols-2.40.2-8.fc42.x86_64 libssh-0.11.1-1.fc42.x86_64 libssh-config-0.11.1-1.fc42.noarch libstdc++-14.2.1-4.fc42.x86_64 libtasn1-4.19.0-9.fc41.x86_64 libtirpc-1.3.5-0.fc41.x86_64 libtool-ltdl-2.4.7-12.fc41.x86_64 libunistring-1.1-8.fc41.x86_64 libuuid-2.40.2-8.fc42.x86_64 libverto-0.3.2-9.fc41.x86_64 libxcrypt-4.4.36-7.fc41.x86_64 libxml2-2.12.8-2.fc41.x86_64 libzstd-1.5.6-2.fc41.x86_64 lua-libs-5.4.6-6.fc41.x86_64 lua-srpm-macros-1-14.fc41.noarch lz4-libs-1.10.0-1.fc41.x86_64 mpfr-4.2.1-5.fc41.x86_64 ncurses-base-6.5-2.20240629.fc41.noarch ncurses-libs-6.5-2.20240629.fc41.x86_64 ocaml-srpm-macros-10-3.fc41.noarch openblas-srpm-macros-2-18.fc41.noarch openldap-2.6.8-5.fc41.x86_64 openssl-libs-3.2.2-8.fc42.x86_64 p11-kit-0.25.5-3.fc41.x86_64 p11-kit-trust-0.25.5-3.fc41.x86_64 package-notes-srpm-macros-0.5-12.fc41.noarch pam-1.6.1-6.fc42.x86_64 pam-libs-1.6.1-6.fc42.x86_64 patch-2.7.6-25.fc41.x86_64 pcre2-10.44-1.fc41.1.x86_64 pcre2-syntax-10.44-1.fc41.1.noarch perl-srpm-macros-1-56.fc41.noarch pkgconf-2.3.0-1.fc42.x86_64 pkgconf-m4-2.3.0-1.fc42.noarch pkgconf-pkg-config-2.3.0-1.fc42.x86_64 popt-1.19-7.fc41.x86_64 publicsuffix-list-dafsa-20240107-4.fc41.noarch pyproject-srpm-macros-1.15.0-1.fc42.noarch python-srpm-macros-3.13-3.fc41.noarch qt5-srpm-macros-5.15.15-1.fc42.noarch qt6-srpm-macros-6.7.2-3.fc41.noarch readline-8.2-11.fc42.x86_64 redhat-rpm-config-296-1.fc42.noarch rpm-4.19.94-1.fc42.x86_64 rpm-build-4.19.94-1.fc42.x86_64 rpm-build-libs-4.19.94-1.fc42.x86_64 rpm-libs-4.19.94-1.fc42.x86_64 rpm-sequoia-1.7.0-2.fc41.x86_64 rust-srpm-macros-26.3-3.fc42.noarch sed-4.9-3.fc41.x86_64 setup-2.15.0-5.fc41.noarch shadow-utils-4.16.0-4.fc42.x86_64 sqlite-libs-3.46.0-4.fc41.x86_64 systemd-libs-256.5-1.fc42.x86_64 tar-1.35-4.fc41.x86_64 unzip-6.0-64.fc41.x86_64 util-linux-2.40.2-8.fc42.x86_64 util-linux-core-2.40.2-8.fc42.x86_64 which-2.21-42.fc41.x86_64 xxhash-libs-0.8.2-3.fc41.x86_64 xz-5.6.2-2.fc41.x86_64 xz-libs-5.6.2-2.fc41.x86_64 zig-srpm-macros-1-3.fc41.noarch zip-3.0-41.fc41.x86_64 zlib-ng-compat-2.1.7-3.fc42.x86_64 zstd-1.5.6-2.fc41.x86_64 Start: buildsrpm Start: rpmbuild -bs Building target platforms: x86_64 Building for target x86_64 warning: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Wrote: /builddir/build/SRPMS/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm RPM build warnings: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Finish: rpmbuild -bs cp: preserving permissions for ‘/var/lib/copr-rpmbuild/results/chroot_scan/var/lib/mock/fedora-rawhide-x86_64-1727860992.197419/root/var/log’: No such file or directory INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-rawhide-x86_64-1727860992.197419/root/var/log/dnf5.log Finish: buildsrpm INFO: Done(/var/lib/copr-rpmbuild/workspace/workdir-97k606er/R-CRAN-ubms/R-CRAN-ubms.spec) Config(child) 0 minutes 14 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_success=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot INFO: Start(/var/lib/copr-rpmbuild/results/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm) Config(fedora-rawhide-x86_64) Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-rawhide-x86_64-1727860992.197419/root. INFO: calling preinit hooks INFO: enabled root cache Start: unpacking root cache Finish: unpacking root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Buildroot is handled by package management from host and used with --installroot: rpm-4.19.1.1-1.fc39.x86_64 rpm-sequoia-1.6.0-1.fc39.x86_64 python3-dnf-4.21.1-1.fc39.noarch python3-dnf-plugins-core-4.9.0-1.fc39.noarch yum-4.21.1-1.fc39.noarch dnf5-5.1.17-2.fc39.x86_64 dnf5-plugins-5.1.17-2.fc39.x86_64 Finish: chroot init Start: build phase for R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm Start: build setup for R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm Building target platforms: x86_64 Building for target x86_64 warning: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Wrote: /builddir/build/SRPMS/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm RPM build warnings: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Updating and loading repositories: fedora 100% | 92.9 KiB/s | 27.1 KiB | 00m00s Copr repository 100% | 77.0 KiB/s | 1.5 KiB | 00m00s Repositories loaded. Package Arch Version Repository Size Installing: R-CRAN-BH noarch 1.84.0.0-1.fc41.copr7349931 copr_base 121.0 MiB R-CRAN-Matrix x86_64 1.7.0-1.fc41.copr7382390 copr_base 8.0 MiB R-CRAN-RSpectra x86_64 0.16.2-1.fc41.copr7752181 copr_base 1.3 MiB R-CRAN-Rcpp x86_64 1.0.13-1.fc41.copr7745410 copr_base 8.4 MiB R-CRAN-RcppArmadillo x86_64 14.0.2.1-1.fc42.copr8016517 copr_base 6.0 MiB R-CRAN-RcppEigen x86_64 0.3.4.0.2-1.fc42.copr8100507 copr_base 9.0 MiB R-CRAN-RcppParallel x86_64 5.1.9-1.fc42.copr7936852 copr_base 1.5 MiB R-CRAN-StanHeaders x86_64 2.32.10-1.fc41.copr7736967 copr_base 9.7 MiB R-CRAN-ggplot2 noarch 3.5.1-1.fc41.copr7361224 copr_base 7.1 MiB R-CRAN-gridExtra noarch 2.3-3.fc41.copr7357925 copr_base 1.6 MiB R-CRAN-loo noarch 2.8.0-1.fc41.copr7705984 copr_base 2.7 MiB R-CRAN-pbapply noarch 1.7.2-1.fc41.copr7350039 copr_base 146.0 KiB R-CRAN-reformulas noarch 0.3.0-1.fc42.copr8100082 copr_base 125.6 KiB R-CRAN-rlang x86_64 1.1.4-1.fc41.copr7531082 copr_base 2.6 MiB R-CRAN-rstan x86_64 2.32.6-1.fc41.copr7480261 copr_base 6.0 MiB R-CRAN-rstantools noarch 2.4.0-1.fc41.copr7356058 copr_base 304.0 KiB R-CRAN-unmarked x86_64 1.4.3-1.fc42.copr7961130 copr_base 5.6 MiB R-core x86_64 4.4.1-5.fc41 fedora 101.5 MiB R-devel x86_64 4.4.1-5.fc41 fedora 0.0 B Installing dependencies: R-CRAN-MASS x86_64 7.3.61-1.fc41.copr7613806 copr_base 1.8 MiB R-CRAN-QuickJSR x86_64 1.4.0-1.fc42.copr8099908 copr_base 3.0 MiB R-CRAN-R6 noarch 2.5.1-1.fc41.copr7349938 copr_base 115.9 KiB R-CRAN-RColorBrewer noarch 1.1.3-1.fc41.copr7349948 copr_base 63.6 KiB R-CRAN-Rdpack noarch 2.6.1-1.fc41.copr7876121 copr_base 1.1 MiB R-CRAN-TMB x86_64 1.9.15-1.fc42.copr8001644 copr_base 3.4 MiB R-CRAN-abind noarch 1.4.8-1.fc42.copr8016475 copr_base 96.2 KiB R-CRAN-backports x86_64 1.5.0-1.fc41.copr7483453 copr_base 211.8 KiB R-CRAN-boot noarch 1.3.31-1.fc42.copr7951483 copr_base 1.1 MiB R-CRAN-callr noarch 3.7.6-1.fc41.copr7356069 copr_base 711.7 KiB R-CRAN-checkmate x86_64 2.3.2-1.fc41.copr7803006 copr_base 1.4 MiB R-CRAN-cli x86_64 3.6.3-1.fc41.copr7649835 copr_base 2.4 MiB R-CRAN-colorspace x86_64 2.1.1-1.fc41.copr7795131 copr_base 4.0 MiB R-CRAN-desc noarch 1.4.3-1.fc41.copr7353609 copr_base 514.2 KiB R-CRAN-distributional noarch 0.5.0-1.fc42.copr8029419 copr_base 723.9 KiB R-CRAN-fansi x86_64 1.0.6-1.fc41.copr7349952 copr_base 625.8 KiB R-CRAN-farver x86_64 2.1.2-1.fc41.copr7442181 copr_base 2.1 MiB R-CRAN-generics noarch 0.1.3-1.fc41.copr7350006 copr_base 160.2 KiB R-CRAN-glue x86_64 1.8.0-1.fc42.copr8094211 copr_base 349.1 KiB R-CRAN-gtable noarch 0.3.5-1.fc41.copr7356060 copr_base 306.7 KiB R-CRAN-inline noarch 0.3.19-1.fc41.copr7349930 copr_base 211.0 KiB R-CRAN-isoband x86_64 0.2.7-1.fc41.copr7351195 copr_base 1.9 MiB R-CRAN-labeling noarch 0.4.3-1.fc41.copr7349947 copr_base 92.7 KiB R-CRAN-lattice x86_64 0.22.6-1.fc41.copr7352639 copr_base 2.0 MiB R-CRAN-lifecycle noarch 1.0.4-1.fc41.copr7354340 copr_base 282.7 KiB R-CRAN-lme4 x86_64 1.1.35.5-1.fc41.copr7705961 copr_base 5.8 MiB R-CRAN-magrittr x86_64 2.0.3-1.fc41.copr7349936 copr_base 417.3 KiB R-CRAN-matrixStats x86_64 1.4.1-1.fc42.copr7998571 copr_base 1.0 MiB R-CRAN-mgcv x86_64 1.9.1-1.fc41.copr7357272 copr_base 4.5 MiB R-CRAN-minqa x86_64 1.2.8-1.fc42.copr7936838 copr_base 237.2 KiB R-CRAN-munsell noarch 0.5.1-1.fc41.copr7353599 copr_base 379.0 KiB R-CRAN-nlme x86_64 3.1.166-1.fc42.copr7936970 copr_base 3.8 MiB R-CRAN-nloptr x86_64 2.1.1-1.fc41.copr7668603 copr_base 1.2 MiB R-CRAN-numDeriv noarch 2016.8.1.1-3.fc41.copr7350037 copr_base 151.0 KiB R-CRAN-pillar noarch 1.9.0-1.fc41.copr7357931 copr_base 1.4 MiB R-CRAN-pkgbuild noarch 1.4.4-1.fc41.copr7357929 copr_base 256.4 KiB R-CRAN-pkgconfig noarch 2.0.3-3.fc41.copr7349937 copr_base 34.0 KiB R-CRAN-posterior noarch 1.6.0-1.fc41.copr7705971 copr_base 1.7 MiB R-CRAN-processx x86_64 3.8.4-1.fc41.copr7353601 copr_base 547.3 KiB R-CRAN-ps x86_64 1.8.0-1.fc42.copr8016516 copr_base 702.6 KiB R-CRAN-rbibutils x86_64 2.2.16-1.fc41.copr7352579 copr_base 2.3 MiB R-CRAN-scales noarch 1.3.0-1.fc41.copr7356067 copr_base 1.1 MiB R-CRAN-tensorA x86_64 0.36.2.1-1.fc41.copr7350295 copr_base 381.7 KiB R-CRAN-tibble x86_64 3.2.1-1.fc41.copr7359525 copr_base 1.7 MiB R-CRAN-utf8 x86_64 1.2.4-1.fc41.copr7349954 copr_base 470.9 KiB R-CRAN-vctrs x86_64 0.6.5-1.fc41.copr7356070 copr_base 2.3 MiB R-CRAN-viridisLite noarch 0.4.2-1.fc41.copr7349928 copr_base 1.3 MiB R-CRAN-withr noarch 3.0.1-1.fc41.copr7810684 copr_base 397.2 KiB R-core-devel x86_64 4.4.1-5.fc41 fedora 394.7 KiB R-java x86_64 4.4.1-5.fc41 fedora 0.0 B R-java-devel x86_64 4.4.1-5.fc41 fedora 0.0 B R-littler x86_64 0.3.19-5.fc41 fedora 158.1 KiB R-rpm-macros noarch 1.2.1-11.fc41 fedora 5.6 KiB abattis-cantarell-vf-fonts noarch 0.301-13.fc41 fedora 192.7 KiB alsa-lib x86_64 1.2.12-2.fc41 fedora 1.4 MiB annobin-docs noarch 12.70-1.fc42 fedora 97.7 KiB annobin-plugin-gcc x86_64 12.70-1.fc42 fedora 985.6 KiB avahi-libs x86_64 0.8-30.fc42 fedora 174.2 KiB brotli x86_64 1.1.0-5.fc41 fedora 31.8 KiB brotli-devel x86_64 1.1.0-5.fc41 fedora 65.6 KiB bzip2-devel x86_64 1.0.8-19.fc41 fedora 309.8 KiB cairo x86_64 1.18.0-4.fc41 fedora 1.7 MiB cairo-devel x86_64 1.18.0-4.fc41 fedora 2.3 MiB cmake-filesystem x86_64 3.28.3-7.fc41 fedora 0.0 B copy-jdk-configs noarch 4.1-6.fc41 fedora 20.3 KiB cpp x86_64 14.2.1-4.fc42 fedora 35.0 MiB cups-libs x86_64 1:2.4.10-7.fc42 fedora 622.9 KiB dbus-libs x86_64 1:1.14.10-4.fc41 fedora 368.9 KiB default-fonts-core-sans noarch 4.1-3.fc42 fedora 11.9 KiB desktop-file-utils x86_64 0.27-2.fc41 fedora 230.4 KiB emacs-filesystem noarch 1:30.0-3.fc41 fedora 0.0 B expat x86_64 2.6.3-1.fc42 fedora 291.5 KiB flexiblas x86_64 3.4.4-3.fc41 fedora 48.5 KiB flexiblas-devel x86_64 3.4.4-3.fc41 fedora 4.8 MiB flexiblas-netlib x86_64 3.4.4-3.fc41 fedora 10.7 MiB flexiblas-netlib64 x86_64 3.4.4-3.fc41 fedora 10.8 MiB flexiblas-openblas-openmp x86_64 3.4.4-3.fc41 fedora 43.3 KiB flexiblas-openblas-openmp64 x86_64 3.4.4-3.fc41 fedora 43.3 KiB fontconfig x86_64 2.15.0-8.fc41 fedora 791.9 KiB fontconfig-devel x86_64 2.15.0-8.fc41 fedora 117.2 KiB fonts-filesystem noarch 1:2.0.5-17.fc41 fedora 0.0 B freetype x86_64 2.13.2-6.fc41 fedora 850.6 KiB freetype-devel x86_64 2.13.2-6.fc41 fedora 7.8 MiB fribidi x86_64 1.0.16-1.fc42 fedora 194.5 KiB gcc x86_64 14.2.1-4.fc42 fedora 104.4 MiB gcc-c++ x86_64 14.2.1-4.fc42 fedora 38.2 MiB gcc-gfortran x86_64 14.2.1-4.fc42 fedora 37.2 MiB gcc-plugin-annobin x86_64 14.2.1-4.fc42 fedora 61.1 KiB gettext x86_64 0.22.5-6.fc41 fedora 5.2 MiB gettext-envsubst x86_64 0.22.5-6.fc41 fedora 74.9 KiB gettext-libs x86_64 0.22.5-6.fc41 fedora 1.7 MiB gettext-runtime x86_64 0.22.5-6.fc41 fedora 481.3 KiB glib2 x86_64 2.82.1-2.fc42 fedora 14.7 MiB glib2-devel x86_64 2.82.1-2.fc42 fedora 15.7 MiB glibc-devel x86_64 2.40.9000-1.fc42 fedora 37.8 KiB glibc-headers-x86 noarch 2.40.9000-1.fc42 fedora 2.2 MiB gnutls x86_64 3.8.7-4.fc42 fedora 3.2 MiB google-noto-fonts-common noarch 20240901-1.fc42 fedora 17.5 KiB google-noto-sans-vf-fonts noarch 20240901-1.fc42 fedora 1.2 MiB graphite2 x86_64 1.3.14-16.fc41 fedora 192.0 KiB graphite2-devel x86_64 1.3.14-16.fc41 fedora 49.1 KiB harfbuzz x86_64 10.0.1-1.fc42 fedora 2.7 MiB harfbuzz-cairo x86_64 10.0.1-1.fc42 fedora 52.3 KiB harfbuzz-devel x86_64 10.0.1-1.fc42 fedora 5.1 MiB harfbuzz-icu x86_64 10.0.1-1.fc42 fedora 19.5 KiB hwloc-libs x86_64 2.11.2-1.fc42 fedora 2.9 MiB java-21-openjdk x86_64 1:21.0.4.0.7-2.fc41 fedora 1.1 MiB java-21-openjdk-devel x86_64 1:21.0.4.0.7-2.fc41 fedora 11.2 MiB java-21-openjdk-headless x86_64 1:21.0.4.0.7-2.fc41 fedora 204.9 MiB javapackages-filesystem noarch 6.3.1-1.fc42 fedora 1.9 KiB jbigkit-libs x86_64 2.1-30.fc41 fedora 117.6 KiB kernel-headers x86_64 6.11.0-63.fc42 fedora 6.4 MiB less x86_64 661-2.fc41 fedora 405.3 KiB libICE x86_64 1.1.1-4.fc41 fedora 181.2 KiB libRmath x86_64 4.4.1-5.fc41 fedora 246.8 KiB libRmath-devel x86_64 4.4.1-5.fc41 fedora 17.4 KiB libSM x86_64 1.2.4-4.fc41 fedora 97.3 KiB libX11 x86_64 1.8.10-2.fc42 fedora 1.3 MiB libX11-common noarch 1.8.10-2.fc42 fedora 1.1 MiB libX11-devel x86_64 1.8.10-2.fc42 fedora 1.0 MiB libX11-xcb x86_64 1.8.10-2.fc42 fedora 15.0 KiB libXau x86_64 1.0.11-7.fc41 fedora 66.9 KiB libXau-devel x86_64 1.0.11-7.fc41 fedora 6.4 KiB libXcomposite x86_64 0.4.6-4.fc41 fedora 44.5 KiB libXext x86_64 1.3.6-2.fc41 fedora 90.1 KiB libXext-devel x86_64 1.3.6-2.fc41 fedora 98.9 KiB libXft x86_64 2.3.8-7.fc41 fedora 164.5 KiB libXft-devel x86_64 2.3.8-7.fc41 fedora 31.7 KiB libXi x86_64 1.8.2-1.fc42 fedora 80.7 KiB libXmu x86_64 1.2.1-2.fc41 fedora 191.5 KiB libXrender x86_64 0.9.11-7.fc41 fedora 50.1 KiB libXrender-devel x86_64 0.9.11-7.fc41 fedora 50.1 KiB libXt x86_64 1.3.0-4.fc41 fedora 429.9 KiB libXtst x86_64 1.2.5-1.fc41 fedora 33.6 KiB libb2 x86_64 0.98.1-12.fc41 fedora 42.2 KiB libblkid-devel x86_64 2.40.2-8.fc42 fedora 44.9 KiB libdatrie x86_64 0.2.13-10.fc41 fedora 57.9 KiB libdeflate x86_64 1.21-2.fc41 fedora 117.0 KiB libdeflate-devel x86_64 1.21-2.fc41 fedora 25.7 KiB libffi-devel x86_64 3.4.6-3.fc42 fedora 33.1 KiB libfontenc x86_64 1.1.8-2.fc41 fedora 67.0 KiB libgfortran x86_64 14.2.1-4.fc42 fedora 3.0 MiB libicu x86_64 74.2-2.fc41 fedora 34.9 MiB libicu-devel x86_64 74.2-2.fc41 fedora 5.6 MiB libjpeg-turbo x86_64 3.0.4-1.fc42 fedora 789.1 KiB liblerc x86_64 4.0.0-7.fc41 fedora 607.5 KiB libmount-devel x86_64 2.40.2-8.fc42 fedora 63.5 KiB libmpc x86_64 1.3.1-6.fc41 fedora 164.7 KiB libpng x86_64 2:1.6.44-1.fc42 fedora 245.8 KiB libpng-devel x86_64 2:1.6.44-1.fc42 fedora 886.0 KiB libquadmath x86_64 14.2.1-4.fc42 fedora 325.9 KiB libquadmath-devel x86_64 14.2.1-4.fc42 fedora 21.9 KiB libselinux-devel x86_64 3.7-6.fc42 fedora 126.5 KiB libsepol-devel x86_64 3.7-3.fc42 fedora 120.3 KiB libstdc++-devel x86_64 14.2.1-4.fc42 fedora 15.4 MiB libtextstyle x86_64 0.22.5-6.fc41 fedora 195.6 KiB libthai x86_64 0.1.29-9.fc41 fedora 783.5 KiB libtiff x86_64 4.6.0-6.fc42 fedora 606.0 KiB libtirpc-devel x86_64 1.3.5-0.fc41 fedora 251.6 KiB libwebp x86_64 1.4.0-4.fc41 fedora 822.6 KiB libxcb x86_64 1.17.0-2.fc41 fedora 1.1 MiB libxcb-devel x86_64 1.17.0-2.fc41 fedora 2.7 MiB libxcrypt-devel x86_64 4.4.36-7.fc41 fedora 30.3 KiB libxml2-devel x86_64 2.12.8-2.fc41 fedora 3.4 MiB lksctp-tools x86_64 1.0.19-9.fc41 fedora 275.2 KiB lua x86_64 5.4.6-6.fc41 fedora 601.7 KiB lua-posix x86_64 36.2.1-7.fc41 fedora 599.8 KiB make x86_64 1:4.4.1-8.fc41 fedora 1.8 MiB mkfontscale x86_64 1.2.3-1.fc41 fedora 49.2 KiB mpdecimal x86_64 2.5.1-16.fc41 fedora 204.9 KiB nettle x86_64 3.10-3.fc41 fedora 793.0 KiB nspr x86_64 4.35.0-29.fc42 fedora 320.4 KiB nss x86_64 3.104.0-1.fc42 fedora 1.9 MiB nss-softokn x86_64 3.104.0-1.fc42 fedora 1.9 MiB nss-softokn-freebl x86_64 3.104.0-1.fc42 fedora 783.6 KiB nss-sysinit x86_64 3.104.0-1.fc42 fedora 22.2 KiB nss-util x86_64 3.104.0-1.fc42 fedora 205.1 KiB openblas x86_64 0.3.26-5.fc41 fedora 96.0 KiB openblas-openmp x86_64 0.3.26-5.fc41 fedora 39.4 MiB openblas-openmp64 x86_64 0.3.26-5.fc41 fedora 39.5 MiB pango x86_64 1.54.0-2.fc41 fedora 996.2 KiB pcre2-devel x86_64 10.44-1.fc41.1 fedora 2.0 MiB pcre2-utf16 x86_64 10.44-1.fc41.1 fedora 590.1 KiB pcre2-utf32 x86_64 10.44-1.fc41.1 fedora 562.0 KiB pixman x86_64 0.43.4-2.fc41 fedora 718.1 KiB pixman-devel x86_64 0.43.4-2.fc41 fedora 49.4 KiB python-pip-wheel noarch 24.2-2.fc42 fedora 1.2 MiB python3 x86_64 3.13.0~rc2-3.fc42 fedora 31.8 KiB python3-libs x86_64 3.13.0~rc2-3.fc42 fedora 40.3 MiB python3-packaging noarch 24.1-2.fc41 fedora 422.3 KiB sysprof-capture-devel x86_64 47.0-1.fc42 fedora 273.2 KiB tbb x86_64 2021.13.0-2.fc41 fedora 440.8 KiB tbb-bind x86_64 2021.13.0-2.fc41 fedora 23.7 KiB tbb-devel x86_64 2021.13.0-2.fc41 fedora 1.3 MiB tcl x86_64 1:8.6.14-2.fc41 fedora 4.2 MiB tcl-devel x86_64 1:8.6.14-2.fc41 fedora 791.3 KiB tk x86_64 1:8.6.14-2.fc41 fedora 3.6 MiB tk-devel x86_64 1:8.6.14-2.fc41 fedora 984.9 KiB tre x86_64 0.8.0-45.20140228gitc2f5d13.fc41 fedora 75.9 KiB tre-common noarch 0.8.0-45.20140228gitc2f5d13.fc41 fedora 81.0 KiB tre-devel x86_64 0.8.0-45.20140228gitc2f5d13.fc41 fedora 10.7 KiB ttmkfdir x86_64 3.0.9-71.fc41 fedora 122.7 KiB tzdata noarch 2024a-9.fc41 fedora 1.7 MiB tzdata-java noarch 2024a-9.fc41 fedora 101.7 KiB xdg-utils noarch 1.2.1-2.fc41 fedora 346.3 KiB xml-common noarch 0.6.3-65.fc41 fedora 78.4 KiB xorg-x11-fonts-Type1 noarch 7.5-39.fc41 fedora 863.3 KiB xorg-x11-proto-devel noarch 2024.1-3.fc41 fedora 1.7 MiB xz-devel x86_64 1:5.6.2-2.fc41 fedora 255.6 KiB zlib-ng-compat-devel x86_64 2.1.7-3.fc42 fedora 106.8 KiB Transaction Summary: Installing: 229 packages Total size of inbound packages is 345 MiB. Need to download 345 MiB. After this operation 1 GiB will be used (install 1 GiB, remove 0 B). [ 1/229] R-CRAN-RSpectra-0:0.16.2-1.fc 100% | 25.8 MiB/s | 449.9 KiB | 00m00s [ 2/229] R-CRAN-Matrix-0:1.7.0-1.fc41. 100% | 119.1 MiB/s | 4.3 MiB | 00m00s [ 3/229] R-CRAN-Rcpp-0:1.0.13-1.fc41.c 100% | 83.7 MiB/s | 2.0 MiB | 00m00s [ 4/229] R-CRAN-BH-0:1.84.0.0-1.fc41.c 100% | 177.6 MiB/s | 9.8 MiB | 00m00s [ 5/229] R-CRAN-RcppArmadillo-0:14.0.2 100% | 53.0 MiB/s | 921.9 KiB | 00m00s [ 6/229] R-CRAN-RcppParallel-0:5.1.9-1 100% | 21.4 MiB/s | 328.8 KiB | 00m00s [ 7/229] R-CRAN-StanHeaders-0:2.32.10- 100% | 221.8 MiB/s | 1.6 MiB | 00m00s [ 8/229] R-CRAN-ggplot2-0:3.5.1-1.fc41 100% | 249.9 MiB/s | 4.7 MiB | 00m00s [ 9/229] R-CRAN-gridExtra-0:2.3-3.fc41 100% | 40.0 MiB/s | 1.0 MiB | 00m00s [ 10/229] R-CRAN-loo-0:2.8.0-1.fc41.cop 100% | 75.5 MiB/s | 1.7 MiB | 00m00s [ 11/229] R-CRAN-pbapply-0:1.7.2-1.fc41 100% | 14.5 MiB/s | 118.9 KiB | 00m00s [ 12/229] R-CRAN-rstantools-0:2.4.0-1.f 100% | 25.1 MiB/s | 179.7 KiB | 00m00s [ 13/229] R-CRAN-rlang-0:1.1.4-1.fc41.c 100% | 119.2 MiB/s | 1.7 MiB | 00m00s [ 14/229] R-CRAN-rstan-0:2.32.6-1.fc41. 100% | 144.9 MiB/s | 2.0 MiB | 00m00s [ 15/229] R-CRAN-RcppEigen-0:0.3.4.0.2- 100% | 239.3 MiB/s | 1.4 MiB | 00m00s [ 16/229] R-devel-0:4.4.1-5.fc41.x86_64 100% | 1.7 MiB/s | 10.5 KiB | 00m00s [ 17/229] R-core-0:4.4.1-5.fc41.x86_64 100% | 369.1 MiB/s | 65.3 MiB | 00m00s [ 18/229] R-CRAN-reformulas-0:0.3.0-1.f 100% | 543.1 KiB/s | 103.2 KiB | 00m00s [ 19/229] R-CRAN-lattice-0:0.22.6-1.fc4 100% | 203.8 MiB/s | 1.4 MiB | 00m00s [ 20/229] flexiblas-netlib-0:3.4.4-3.fc 100% | 268.2 MiB/s | 3.2 MiB | 00m00s [ 21/229] R-littler-0:0.3.19-5.fc41.x86 100% | 23.2 MiB/s | 71.3 KiB | 00m00s [ 22/229] tbb-0:2021.13.0-2.fc41.x86_64 100% | 80.2 MiB/s | 164.2 KiB | 00m00s [ 23/229] R-CRAN-MASS-0:7.3.61-1.fc41.c 100% | 196.5 MiB/s | 1.2 MiB | 00m00s [ 24/229] R-CRAN-glue-0:1.8.0-1.fc42.co 100% | 42.7 MiB/s | 174.9 KiB | 00m00s [ 25/229] R-CRAN-gtable-0:0.3.5-1.fc41. 100% | 112.5 MiB/s | 230.3 KiB | 00m00s [ 26/229] R-CRAN-lifecycle-0:1.0.4-1.fc 100% | 63.6 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R-CRAN-lme4-0:1.1.35.5-1.fc41 100% | 269.6 MiB/s | 4.0 MiB | 00m00s [ 40/229] R-CRAN-Rdpack-0:2.6.1-1.fc41. 100% | 260.7 MiB/s | 801.0 KiB | 00m00s [ 41/229] R-core-devel-0:4.4.1-5.fc41.x 100% | 46.6 MiB/s | 95.5 KiB | 00m00s [ 42/229] R-java-devel-0:4.4.1-5.fc41.x 100% | 10.3 MiB/s | 10.5 KiB | 00m00s [ 43/229] R-rpm-macros-0:1.2.1-11.fc41. 100% | 11.0 MiB/s | 11.3 KiB | 00m00s [ 44/229] cairo-0:1.18.0-4.fc41.x86_64 100% | 173.3 MiB/s | 709.9 KiB | 00m00s [ 45/229] glib2-0:2.82.1-2.fc42.x86_64 100% | 169.0 MiB/s | 3.0 MiB | 00m00s [ 46/229] less-0:661-2.fc41.x86_64 100% | 61.3 MiB/s | 188.5 KiB | 00m00s [ 47/229] libRmath-0:4.4.1-5.fc41.x86_6 100% | 60.5 MiB/s | 123.9 KiB | 00m00s [ 48/229] libX11-0:1.8.10-2.fc42.x86_64 100% | 158.6 MiB/s | 649.7 KiB | 00m00s [ 49/229] libXmu-0:1.2.1-2.fc41.x86_64 100% | 38.1 MiB/s | 78.0 KiB | 00m00s [ 50/229] libXt-0:1.3.0-4.fc41.x86_64 100% | 57.8 MiB/s | 177.4 KiB | 00m00s [ 51/229] libdeflate-0:1.21-2.fc41.x86_ 100% | 32.9 MiB/s | 67.4 KiB | 00m00s [ 52/229] R-CRAN-unmarked-0:1.4.3-1.fc4 100% | 8.6 MiB/s | 2.9 MiB | 00m00s [ 53/229] libjpeg-turbo-0:3.0.4-1.fc42. 100% | 37.2 MiB/s | 228.9 KiB | 00m00s [ 54/229] libpng-2:1.6.44-1.fc42.x86_64 100% | 29.5 MiB/s | 120.7 KiB | 00m00s [ 55/229] libtiff-0:4.6.0-6.fc42.x86_64 100% | 41.4 MiB/s | 212.0 KiB | 00m00s [ 56/229] libicu-0:74.2-2.fc41.x86_64 100% | 266.4 MiB/s | 10.4 MiB | 00m00s [ 57/229] pango-0:1.54.0-2.fc41.x86_64 100% | 28.3 MiB/s | 347.5 KiB | 00m00s [ 58/229] tk-1:8.6.14-2.fc41.x86_64 100% | 231.1 MiB/s | 1.6 MiB | 00m00s [ 59/229] tcl-1:8.6.14-2.fc41.x86_64 100% | 122.5 MiB/s | 1.1 MiB | 00m00s [ 60/229] tre-0:0.8.0-45.20140228gitc2f 100% | 42.7 MiB/s | 43.7 KiB | 00m00s [ 61/229] xdg-utils-0:1.2.1-2.fc41.noar 100% | 38.7 MiB/s | 79.3 KiB | 00m00s [ 62/229] flexiblas-0:3.4.4-3.fc41.x86_ 100% | 24.7 MiB/s | 25.3 KiB | 00m00s [ 63/229] flexiblas-openblas-openmp-0:3 100% | 16.8 MiB/s | 17.2 KiB | 00m00s [ 64/229] libquadmath-0:14.2.1-4.fc42.x 100% | 65.9 MiB/s | 202.6 KiB | 00m00s [ 65/229] libgfortran-0:14.2.1-4.fc42.x 100% | 183.2 MiB/s | 937.9 KiB | 00m00s [ 66/229] R-CRAN-cli-0:3.6.3-1.fc41.cop 100% | 131.8 MiB/s | 1.3 MiB | 00m00s [ 67/229] R-CRAN-nlme-0:3.1.166-1.fc42. 100% | 202.1 MiB/s | 2.4 MiB | 00m00s [ 68/229] R-CRAN-R6-0:2.5.1-1.fc41.copr 100% | 31.1 MiB/s | 95.5 KiB | 00m00s [ 69/229] R-CRAN-RColorBrewer-0:1.1.3-1 100% | 30.6 MiB/s | 62.7 KiB | 00m00s [ 70/229] R-CRAN-farver-0:2.1.2-1.fc41. 100% | 222.0 MiB/s | 1.3 MiB | 00m00s [ 71/229] R-CRAN-labeling-0:0.4.3-1.fc4 100% | 18.6 MiB/s | 76.2 KiB | 00m00s [ 72/229] R-CRAN-TMB-0:1.9.15-1.fc42.co 100% | 5.8 MiB/s | 869.7 KiB | 00m00s [ 73/229] R-CRAN-munsell-0:0.5.1-1.fc41 100% | 81.7 MiB/s | 251.0 KiB | 00m00s [ 74/229] R-CRAN-fansi-0:1.0.6-1.fc41.c 100% | 85.2 MiB/s | 349.2 KiB | 00m00s [ 75/229] R-CRAN-viridisLite-0:0.4.2-1. 100% | 178.4 MiB/s | 1.2 MiB | 00m00s [ 76/229] R-CRAN-pillar-0:1.9.0-1.fc41. 100% | 121.7 MiB/s | 623.3 KiB | 00m00s [ 77/229] R-CRAN-pkgconfig-0:2.0.3-3.fc 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make-1:4.4.1-8.fc41.x86_64 100% | 114.5 MiB/s | 586.1 KiB | 00m00s [ 91/229] fontconfig-0:2.15.0-8.fc41.x8 100% | 65.9 MiB/s | 269.9 KiB | 00m00s [ 92/229] freetype-0:2.13.2-6.fc41.x86_ 100% | 80.2 MiB/s | 410.7 KiB | 00m00s [ 93/229] libXext-0:1.3.6-2.fc41.x86_64 100% | 9.5 MiB/s | 39.1 KiB | 00m00s [ 94/229] libXrender-0:0.9.11-7.fc41.x8 100% | 6.7 MiB/s | 27.5 KiB | 00m00s [ 95/229] libxcb-0:1.17.0-2.fc41.x86_64 100% | 38.9 MiB/s | 239.0 KiB | 00m00s [ 96/229] pixman-0:0.43.4-2.fc41.x86_64 100% | 41.0 MiB/s | 294.1 KiB | 00m00s [ 97/229] java-21-openjdk-devel-1:21.0. 100% | 185.4 MiB/s | 5.0 MiB | 00m00s [ 98/229] libX11-common-0:1.8.10-2.fc42 100% | 21.5 MiB/s | 175.9 KiB | 00m00s [ 99/229] gnutls-0:3.8.7-4.fc42.x86_64 100% | 111.7 MiB/s | 1.1 MiB | 00m00s [100/229] libICE-0:1.1.1-4.fc41.x86_64 100% | 36.5 MiB/s | 74.7 KiB | 00m00s [101/229] libSM-0:1.2.4-4.fc41.x86_64 100% | 21.1 MiB/s | 43.2 KiB | 00m00s [102/229] jbigkit-libs-0:2.1-30.fc41.x8 100% | 17.4 MiB/s | 53.3 KiB | 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Finish: build setup for R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm Start: rpmbuild R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm Building target platforms: x86_64 Building for target x86_64 warning: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Executing(%mkbuilddir): /bin/sh -e /var/tmp/rpm-tmp.EGOHrX + umask 022 + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + test -d /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + /usr/bin/rm -rf /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + /usr/bin/mkdir -p /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + /usr/bin/mkdir -p /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/SPECPARTS + RPM_EC=0 ++ jobs -p + exit 0 Executing(%prep): /bin/sh -e /var/tmp/rpm-tmp.qSYqjH + umask 022 + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + rm -rf ubms + /usr/bin/mkdir -p ubms + cd ubms + /usr/lib/rpm/rpmuncompress -x /builddir/build/SOURCES/ubms_1.2.7.tar.gz + STATUS=0 + '[' 0 -ne 0 ']' + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w . + find -type f -executable -exec grep -Iq . '{}' ';' -exec sed -i -e '$a\' '{}' ';' + '[' -d ubms/src ']' + find ubms/src -type f -exec sed -i s@/usr/bin/strip@/usr/bin/true@g '{}' ';' + '[' -d ubms/src ']' + find ubms/src/Makevars ubms/src/Makevars.win -type f -exec sed -i s@-g0@@g '{}' ';' + find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' '{}' ';' + RPM_EC=0 ++ jobs -p + exit 0 Executing(%build): /bin/sh -e /var/tmp/rpm-tmp.5PtxBW + umask 022 + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd ubms + RPM_EC=0 ++ jobs -p + exit 0 Executing(%install): /bin/sh -e /var/tmp/rpm-tmp.jM593F + umask 022 + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + '[' /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT '!=' / ']' + rm -rf /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT ++ dirname /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT + mkdir -p /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + mkdir /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd ubms + mkdir -p /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT/usr/local/lib/R/library + /usr/bin/R CMD INSTALL -l /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT/usr/local/lib/R/library ubms * installing *source* package ‘ubms’ ... ** package ‘ubms’ successfully unpacked and MD5 sums checked ** using staged installation Registered S3 methods overwritten by 'RcppEigen': method from predict.fastLm RcppArmadillo print.fastLm RcppArmadillo summary.fastLm RcppArmadillo print.summary.fastLm RcppArmadillo Warning message: In .warning_nowrite(file.path(basename(pkgdir), ...)) : 'ubms/src/Makevars' already exists. Not overwritten by rstantools.FALSE ** libs using C++ compiler: ‘g++ (GCC) 14.2.1 20240912 (Red Hat 14.2.1-4)’ g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c RcppExports.cpp -o RcppExports.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/RcppEigen/include/RcppEigenForward.h:28, from /usr/local/lib/R/library/RcppEigen/include/RcppEigen.h:25, from RcppExports.cpp:5: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/RcppEigen/include/RcppEigenForward.h:29: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c exp_counts_occu.cpp -o exp_counts_occu.o g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c loglik.cpp -o loglik.o g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c simz.cpp -o simz.o g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c stanExports_colext.cc -o stanExports_colext.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:3, from stanExports_colext.h:23, from stanExports_colext.cc:5: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:18, from /usr/local/lib/R/library/BH/include/boost/shared_ptr.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/time_clock.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:15, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:4: /usr/local/lib/R/library/BH/include/boost/smart_ptr/detail/shared_count.hpp:361:33: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 361 | explicit shared_count( std::auto_ptr & r ): pi_( new sp_counted_impl_p( r.get() ) ) | ^~~~~~~~ In file included from /usr/include/c++/14/memory:78, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:7: /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:251:65: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 251 | template< class T, class R > struct sp_enable_if_auto_ptr< std::auto_ptr< T >, R > | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:508:31: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 508 | explicit shared_ptr( std::auto_ptr & r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:521:22: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 521 | shared_ptr( std::auto_ptr && r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:604:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 604 | shared_ptr & operator=( std::auto_ptr & r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:613:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 613 | shared_ptr & operator=( std::auto_ptr && r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function ‘boost::shared_ptr& boost::shared_ptr::operator=(std::auto_ptr<_Up>&&)’: /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:615:38: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 615 | this_type( static_cast< std::auto_ptr && >( r ) ).swap( *this ); | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from ‘struct Eigen::internal::traits > >’ 19 | template struct traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from ‘class Eigen::SolverBase > >’ 68 | class SolverBase : public EigenBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from ‘class Eigen::LDLT >’ 59 | template class LDLT | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from ‘class Eigen::LDLT >’ 69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from ‘class Eigen::LDLT >’ 287 | TmpMatrixType m_temporary; | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:29: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:41: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:45: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:26: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:34: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_array.hpp:37:49: required from here 37 | Eigen::VectorXd v = Eigen::VectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:28: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:39: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:53: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:72: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:77: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:17: required from here 71 | A.diagonal().array() -= mu; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:29: required from here 71 | A.diagonal().array() -= mu; | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:22: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:38: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:178:58: required from here 178 | alpha = Eigen::VectorXd::Constant(_p_max - 1, normA); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::internal::member_minCoeff, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::internal::member_minCoeff, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::internal::member_minCoeff, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, Eigen::internal::member_minCoeff, 0>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:203:38: required from here 203 | int cost = c.colwise().minCoeff().minCoeff(&m); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/one_hot_row_vector.hpp:25:52: required from here 25 | Eigen::RowVectorXd ret = Eigen::RowVectorXd::Zero(K); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:13:64: required from here 13 | : m_(Eigen::VectorXd::Zero(n)), m2_(Eigen::MatrixXd::Zero(n, n)) { | ~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:26:31: required from here 26 | Eigen::VectorXd delta(q - m_); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:38: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:37:40: required from here 37 | covar = m2_ / (num_samples_ - 1.0); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_var_estimator.hpp:28:30: required from here 28 | m2_ += delta.cwiseProduct(q - m_); | ~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here 77 | Eigen::Map(dz_dt.data(), dz_dt.size()) = f_y_t; | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:13, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:43: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combination(std::vector&, const int&, const int&, const int&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:73:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 73 | for (std::size_t i = 0; i < p - 1; i++) { | ~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:79:16: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 79 | } while (k < x); | ~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:102:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 102 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:105:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 105 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::increment(std::vector&, const int&, const double&, const std::vector&, std::vector&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:126:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 126 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 132 | while ((first_zero < index.size()) && index[first_zero]) { | ~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 135 | if (first_zero == index.size()) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:143:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 143 | for (std::size_t i = 0; i != first_zero + 1; i++) { | ~~^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:168:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 168 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here 40 | coupled_state.size()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/mpl/aux_/na_assert.hpp:23, from /usr/local/lib/R/library/BH/include/boost/mpl/arg.hpp:25, from /usr/local/lib/R/library/BH/include/boost/mpl/placeholders.hpp:24, from /usr/local/lib/R/library/BH/include/boost/mpl/apply.hpp:24, from /usr/local/lib/R/library/BH/include/boost/serialization/array_optimization.hpp:18, from /usr/local/lib/R/library/BH/include/boost/serialization/array_wrapper.hpp:21, from /usr/local/lib/R/library/BH/include/boost/serialization/array.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:22, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/vector.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint.hpp:25, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:16: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp: At global scope: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: warning: unnecessary parentheses in declaration of ‘assert_arg’ [-Wparentheses] 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ | - 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ | - /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of ‘assert_not_arg’ [-Wparentheses] 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | - 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ | - In file included from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/traits.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:27: /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:111:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 111 | public std::iterator { | ^~~~~~~~ In file included from /usr/include/c++/14/bits/stl_algobase.h:65, from /usr/include/c++/14/bits/specfun.h:43, from /usr/include/c++/14/cmath:3898, from /usr/local/lib/R/library/Rcpp/include/Rcpp/platform/compiler.h:100, from /usr/local/lib/R/library/Rcpp/include/Rcpp/r/headers.h:66, from /usr/local/lib/R/library/Rcpp/include/RcppCommon.h:30, from /usr/local/lib/R/library/Rcpp/include/Rcpp.h:27, from stanExports_colext.cc:3: /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:149:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 149 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:204:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 204 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/invoke.hpp:52, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/adapter/fused.hpp:17, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/generation/make_fused.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/include/make_fused.hpp:11, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:28, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33: /usr/local/lib/R/library/BH/include/boost/get_pointer.hpp:48:40: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 48 | template T * get_pointer(std::auto_ptr const& p) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:38:59: required from here 38 | Eigen::VectorXd stddev = S_ldlt.vectorD().array().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 5>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:75: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:76: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:135:41: required from here 135 | Eigen::VectorXd(F.transpose() * theta_t), V_ldlt, rng); | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_hidden_state_prob.hpp:77:52: required from here 77 | alphas.col(n) = alphas.col(n).cwiseProduct(beta); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_latent_rng.hpp:71:73: required from here 71 | probs_vec = alphas.col(n_transitions) / alphas.col(n_transitions).sum(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::TriangularView >, 2>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::TriangularView >, 2>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::TriangularView >, 2>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:42: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::TriangularView >, 2>, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:25:32: required from here 25 | S_inv = ldlt_of_S.solve(S_inv); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:47: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:54: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:109:64: required from here 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Matrix >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: recursively required by substitution of ‘template const Eigen::internal::triangular_solve_retval >, 6>, Other> Eigen::TriangularViewImpl >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase&) const [with int Side = ; Other = ]’ 108 | * (D_ldlt.matrixU().solve( | ~~~~~~~~~~~~~~~~~~~~~~^ 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from ‘struct Eigen::internal::accessors_level >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 32 | enum { has_direct_access = (traits::Flags & DirectAccessBit) ? 1 : 0, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:43: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:51: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:52: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/multinomial_logit_lpmf.hpp:39:0: required from here 39 | lp += lgamma(1 + ns_map.sum()) - lgamma(1 + ns_map).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_ccdf_log.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob.hpp:240, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:16: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp: In function ‘stan::return_type_t stan::math::normal_lccdf(const T_y&, const T_loc&, const T_scale&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: ‘-Wmisleading-indentation’ is disabled from this point onwards, since column-tracking was disabled due to the size of the code/headers 68 | } else if (scaled_diff > 8.25 * INV_SQRT_TWO) { /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: adding ‘-flarge-source-files’ will allow for more column-tracking support, at the expense of compilation time and memory /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp: In member function ‘virtual std::vector > stan::io::dump::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 694 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 707 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here 102 | if (C_adj.size() > 0) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here 111 | = D_adj.adjoint().template triangularView(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1, -1, false>, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here 116 | D_adj.diagonal() *= 0.5; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from ‘class Eigen::RefBase, 0, Eigen::OuterStride<> > >’ 59 | template class RefBase | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from ‘class Eigen::Ref, 0, Eigen::OuterStride<> >’ 281 | template class Ref | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from ‘class Eigen::LLT, 0, Eigen::OuterStride<> >, 1>’ 76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:142:0: required from here 142 | check_pos_definite("cholesky_decompose", "m", L_factor); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here 144 | L_A.template triangularView().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_factor_constrain.hpp:42:0: required from here 42 | y_val.row(m).head(m) = x.val().segment(pos, m); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of ‘template static std::true_type stan::is_base_pointer_convertible >::f(const Eigen::EigenBase*) [with OtherDerived = ]’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible >’ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from ‘struct stan::is_eigen >’ 21 | : bool_constant::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of ‘template class stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix]’ 301 | (is_eigen::value || is_kernel_expression_and_not_scalar::value) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 1>’ 148 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 222 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from ‘class stan::math::arena_matrix, void>’ 129 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from ‘class stan::math::vari_value, void>’ 814 | using InnerIterator = typename arena_matrix::InnerIterator; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from ‘const auto& stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 419 | inline const auto& val() const noexcept { return vi_->val(); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from ‘class Eigen::Tridiagonalization >’ 97 | >::type SubDiagonalReturnType; | ^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from ‘class Eigen::SelfAdjointEigenSolver >’ 111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here 40 | arena_t eigenvals = solver.eigenvalues(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here 27 | g = x.adj(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0> > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:51:0: required from here 51 | reverse_pass_callback([arena_M, log_det, arena_M_inv_transpose]() mutable { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:73:0: required from here 73 | vector_d diff = (x_d.array() - x_d.maxCoeff()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here 81 | Eigen::Map(softmax_x_d_array, a_size) = softmax_x_d.array() / sum; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:50:0: required from here 50 | arena_powers[0] = Eigen::MatrixXd::Identity(N, N); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:53:0: required from here 53 | arena_powers[i] = arena_powers[1] * arena_powers[i - 1]; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:63:0: required from here 63 | adj_M += adj_C * arena_powers[i - 1].transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here 67 | Eigen::Map(variRefB_, M_, N_).adj() += adjB; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from here 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:55:0: required from here 55 | L.col(0).tail(pull) = CPCs.val().head(pull); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:56:0: required from here 56 | arena_acc.tail(pull) = 1.0 - CPCs.val().head(pull).array().square(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:63:0: required from here 63 | L.col(i).tail(pull) = cpc_seg * arena_acc.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_cov_matrix.hpp:56:0: required from here 56 | sds.adj() += (prod.adj().cwiseProduct(corr_L.val())).rowwise().sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/rows_dot_self.hpp:41:0: required from here 41 | x.adj() += (2 * res.adj()).asDiagonal() * x.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0, Eigen::Stride<0, 0> >, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here 56 | arena_Fp.diagonal().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here 70 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from ‘struct Eigen::internal::traits, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 278 | typedef typename DiagonalVectorType::Scalar Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from ‘class Eigen::DiagonalBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 18 | class DiagonalBase : public EigenBase | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from ‘class Eigen::DiagonalWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 293 | class DiagonalWrapper | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:63:0: required from here 63 | + arena_U * arena_D.asDiagonal().inverse() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here 80 | v1_map.adj() += di; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:23:0: required from here 23 | vector_d dtrs_vals = dtrs_map.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::val_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here 26 | fx = fx_var.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&):: [with auto:12 = const Eigen::Matrix, -1, 1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::; Args = {const Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from ‘auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]’ 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/algebra_solver_fp.hpp:101:0: required from here 101 | y_dummy(stan::math::value_of(y)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here 604 | f_y_t_vars.adj() = -Eigen::Map(NV_DATA_S(yB), N_); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/finite_diff_hessian_times_vector_auto.hpp:62:0: required from here 62 | hvp = (grad_forward - grad_backward) / (2 * epsilon); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/initialize.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:49: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function ‘virtual std::vector > stan::io::random_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 111 | for (comp_iter = 0, real_iter = 0; real_iter < val_r.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:182:0: required from here 182 | return normal_fullrank(Eigen::VectorXd(mu_.array().square()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:183:0: required from here 183 | Eigen::MatrixXd(L_chol_.array().square())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:197:0: required from here 197 | return normal_fullrank(Eigen::VectorXd(mu_.array().sqrt()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:198:0: required from here 198 | Eigen::MatrixXd(L_chol_.array().sqrt())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:263:0: required from here 263 | L_chol_.array() /= rhs.L_chol().array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:459:0: required from here 459 | L_grad.diagonal().array() += L_chol_.diagonal().array().inverse(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:370:0: required from here 370 | omega_grad.array() += tmp_mu_grad.array().cwiseProduct(eta.array()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:388:0: required from here 388 | omega_grad.array() = omega_grad.array().cwiseProduct(omega_.array().exp()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/nuts/base_nuts.hpp:175:0: required from here 175 | rho = rho_bck + rho_fwd; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 2>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 2>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 2>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 2>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 2>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:53:0: required from here 53 | z.p = z.inv_e_metric_.llt().matrixU().solve(u); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from ‘auto stan::math::to_matrix(const std::vector&, int, int) [with T = double]’ 133 | return Eigen::Map>( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 134 | &x[0], m, n); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/read_dense_inv_metric.hpp:33:0: required from here 33 | inv_metric = stan::math::to_matrix(dense_vals, num_params, num_params); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here 27 | covar = (n / (n + 5.0)) * covar /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of ‘template typename Eigen::ScalarBinaryOpTraits::Scalar, Eigen::internal::scalar_product_op::Scalar> >::ReturnType Eigen::MatrixBase >::dot(const Eigen::MatrixBase&) const [with OtherDerived = ]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here 27 | var = (n / (n + 5.0)) * var /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:68: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function ‘virtual std::vector > stan::io::array_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 304 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 317 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue_varmat.hpp:145:0: required from here 145 | x_ret_vals.coeffRef(j) = x.val().coeff(row_idx_val, col_idx_vals[j]); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_header.hpp:11, from stanExports_colext.h:25: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp: At global scope: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:159: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(std::vector, std::allocator > >&, std::vector&, std::ostream*) const [with M = model_colext_namespace::model_colext; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 159 | inline math::var log_prob(std::vector& theta, stanExports_colext.h:3633: note: by ‘model_colext_namespace::model_colext::log_prob’ 3633 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:154: warning: ‘double stan::model::model_base_crtp::log_prob(std::vector&, std::vector&, std::ostream*) const [with M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 154 | inline double log_prob(std::vector& theta, std::vector& theta_i, stanExports_colext.h:3633: note: by ‘model_colext_namespace::model_colext::log_prob’ 3633 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:96: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(Eigen::Matrix, -1, 1>&, std::ostream*) const [with M = model_colext_namespace::model_colext; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 96 | inline math::var log_prob(Eigen::Matrix& theta, stanExports_colext.h:3633: note: by ‘model_colext_namespace::model_colext::log_prob’ 3633 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:91: warning: ‘double stan::model::model_base_crtp::log_prob(Eigen::VectorXd&, std::ostream*) const [with M = model_colext_namespace::model_colext; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 91 | inline double log_prob(Eigen::VectorXd& theta, stanExports_colext.h:3633: note: by ‘model_colext_namespace::model_colext::log_prob’ 3633 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:102:18: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0; stan::return_type_t = double]’ 102 | x.unaryExpr([lb, &lp](auto&& xx) { return lb_constrain(xx, lb, lp); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2650:0: required from here 2649 | sigma_state = in__.template read_constrain_lb< 2650 | Eigen::Matrix, jacobian__>(0, 2651 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:83:26: required from ‘auto stan::math::lb_constrain(T&&, L&&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = const int&; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 83 | return eval(x.unaryExpr([lb](auto&& x) { return lb_constrain(x, lb); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:388:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 388 | return stan::math::lb_constrain(this->read(sizes...), lb); stanExports_colext.h:2650:0: required from here 2649 | sigma_state = in__.template read_constrain_lb< 2650 | Eigen::Matrix, jacobian__>(0, 2651 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from ‘auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]’ 107 | return m1 * m2; | ~~~^~~~ stanExports_colext.h:2751:0: required from here 2751 | stan::math::add(stan::math::multiply(X_state, beta_state), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Mat2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_colext.h:2751:0: required from here 2751 | stan::math::add(stan::math::multiply(X_state, beta_state), 2752 | offset_state), "assigning variable logit_psi"); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from ‘struct Eigen::internal::traits >’ 17 | struct traits > : traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar&>(const std::vector&)::; Args = {const std::vector >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:72:21: required from ‘auto stan::math::as_array_or_scalar(T&&) [with T = const std::vector&; stan::require_std_vector_t* = 0; stan::require_not_std_vector_t::type>* = 0]’ 72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | std::forward(v)); | ~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:39: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:43: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:55: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&):: [with auto:10 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&)::; T2 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_t::type> >* = 0; T = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from ‘auto stan::math::fabs(const Container&) [with Container = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_container_st* = 0]’ 66 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:37: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&)::; T2 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_t::type> >* = 0; T = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:49:25: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk)); | ~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:22: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long unsigned int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here 97 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { stanExports_colext.h: In instantiation of ‘void model_colext_namespace::model_colext::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = std::vector; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_colext.h:3661:0: required from here 3661 | unconstrain_array_impl(params_constrained, params_i, 3662 | params_unconstrained, pstream); stanExports_colext.h:2886: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 2886 | int pos__ = std::numeric_limits::min(); stanExports_colext.h: In instantiation of ‘void model_colext_namespace::model_colext::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = Eigen::Matrix; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_colext.h:3671:0: required from here 3671 | unconstrain_array_impl(params_constrained, params_i, 3672 | params_unconstrained, pstream); stanExports_colext.h:2886: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 2886 | int pos__ = std::numeric_limits::min(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp: In instantiation of ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’: stanExports_colext.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1252: warning: variable ‘ret’ set but not used [-Wunused-but-set-variable] 1252 | int ret = stan::services::error_codes::CONFIG; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 182 | Eigen::Matrix b_args(1); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:117:39: required from ‘TupleT stan::math::internal::grad_2F1_impl_ab(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 117 | inner_diff = g_current.array().abs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:204:78: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 204 | grad_tuple_ab = grad_2F1_impl_ab( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 205 | a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:12: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:47:0: required from here 47 | stan::math::check_not_nan(function, "Mean vector", mu); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:74:0: required from here 74 | stan::math::check_not_nan(function, "Cholesky factor", L_chol); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 207 | for (size_t i = 0; i < x.rows(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 208 | for (size_t j = 0; j < x.cols(); j++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:21:0: required from here 21 | stan::math::check_finite("check_finite", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:22:0: required from here 22 | stan::math::check_positive("check_positive", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here 30 | if (!var.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta.hpp:70, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:10: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp: In instantiation of ‘void stan::math::check_less_or_equal(const char*, const char*, const T_y&, const T_high&, Idxs ...) [with T_y = long unsigned int; T_high = long int; stan::require_all_stan_scalar_t* = 0; Idxs = {}]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’ 79 | stan::math::check_less_or_equal("validate_dims", "array_var_context", 80 | elem_dims_total[dims.size()], array_size); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp:39:20: warning: comparison of integer expressions of different signedness: ‘const long unsigned int’ and ‘const long int’ [-Wsign-compare] 39 | if (unlikely(!(y <= high))) { | ~~~^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/compiler_attributes.hpp:9:41: note: in definition of macro ‘unlikely’ 9 | #define unlikely(x) __builtin_expect(!!(x), 0) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:21: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_colext.h:3154:0: required from ‘void model_colext_namespace::model_colext::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3154 | out__.write_free_lb(0, sigma_state); stanExports_colext.h:3652:0: required from here 3652 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:32: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_colext.h:3154:0: required from ‘void model_colext_namespace::model_colext::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3154 | out__.write_free_lb(0, sigma_state); stanExports_colext.h:3652:0: required from here 3652 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_colext.h:3154:0: required from ‘void model_colext_namespace::model_colext::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3154 | out__.write_free_lb(0, sigma_state); stanExports_colext.h:3652:0: required from here 3652 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_colext.h:3154:0: required from ‘void model_colext_namespace::model_colext::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3154 | out__.write_free_lb(0, sigma_state); stanExports_colext.h:3652:0: required from here 3652 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_colext.h:3154:0: required from ‘void model_colext_namespace::model_colext::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3154 | out__.write_free_lb(0, sigma_state); stanExports_colext.h:3652:0: required from here 3652 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp: In instantiation of ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; Eigen::MatrixXd = Eigen::Matrix]’: /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_colext.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: ‘std::vector >::size_type’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 55 | if (p_names.size() != draws.cols()) { /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:71: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 71 | for (size_t i = 0; i < draws.rows(); ++i) { In file included from /usr/local/lib/R/library/BH/include/boost/concept/assert.hpp:35, from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:19, from /usr/local/lib/R/library/BH/include/boost/range/size_type.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/size.hpp:21, from /usr/local/lib/R/library/BH/include/boost/range/functions.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range.hpp:18, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:22: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept >, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:26, from /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:16, from /usr/local/lib/R/library/BH/include/boost/algorithm/string.hpp:23, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:46: /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::token_finderF >; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:98:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FormatterConcept >, boost::algorithm::detail::first_finderF, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:103:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function ‘void boost::algorithm::FormatterConcept::constraints() [with FormatterT = boost::algorithm::detail::const_formatF >; FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 65 | void constraints() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:19: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:330: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 72 | typedef blas_data_mapper ResMapper; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 451 | subdiag = mat.template diagonal<-1>().real(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 1, -1, false>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 191 | _pk.noalias() = -_gk; /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:192:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 192 | auto exp_x = to_arena(arena_x.val().array().exp()); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:193:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 193 | arena_t ret = exp_x + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&):: [with auto:12 = const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_colext.h:2355:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2354 | sigma_state = in__.template read_constrain_lb< 2355 | Eigen::Matrix, jacobian__>(0, 2356 | lp__, n_group_vars_state); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:34:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 34 | auto arena_A_val = to_arena(arena_A.val()); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 36 | using return_t stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 47 | arena_A.adj() += res_adj * arena_B_val.transpose(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&):: [with auto:12 = stan::math::arena_matrix, -1, -1>, void>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 66 | = return_var_matrix_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:14 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), 2434 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:255:7: required from ‘class Eigen::Map >’ 255 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> >&>(arena_matrix, -1, 1> >&):: [with auto:12 = stan::math::arena_matrix, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:128:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 128 | arena_t res = w_val_mat * value_of(b_arena); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:135:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 135 | arena_t res = w_mat_arena.val() * b_arena; stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 114 | using ret_type = return_var_matrix_t; stanExports_colext.h:2439:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2439 | stan::math::add(stan::model::deep_copy(logit_psi), 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_colext.h:2439:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2439 | stan::math::add(stan::model::deep_copy(logit_psi), 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_colext.h:2758:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2758 | stan::math::csr_matrix_times_vector( 2759 | stan::model::rvalue(Zdim_state, "Zdim_state", 2760 | stan::model::index_uni(1)), 2761 | stan::model::rvalue(Zdim_state, "Zdim_state", 2762 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2763 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:583:0: required from ‘auto stan::model::rvalue(Mat&&, const char*, const Idx&, index_omni) [with Mat = const Eigen::Matrix&; Idx = index_min_max; stan::require_dense_dynamic_t* = 0]’ 583 | return rvalue(std::forward(x), name, row_idx); stanExports_colext.h:927:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from ‘auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Matrix&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]’ 187 | return v.segment(slice_start, slice_size); stanExports_colext.h:933:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 35 | check_finite("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 36 | check_finite("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 39 | check_not_nan("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 40 | check_not_nan("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/math/special_functions/beta.hpp:1721, from /usr/local/lib/R/library/BH/include/boost/math/special_functions/binomial.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun.hpp:46, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:14: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp: In instantiation of ‘boost::math::detail::temme_root_finder::temme_root_finder(T, T) [with T = double]’: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: required from ‘T boost::math::detail::temme_method_2_ibeta_inverse(T, T, T, T, T, const Policy&) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 304 | temme_root_finder(-lu, alpha), x, lower, upper, policies::digits() / 2); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:48: required from ‘T boost::math::detail::ibeta_inv_imp(T, T, T, T, const Policy&, T*) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 615 | x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:30: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(T1, T2, T3, T4*, const Policy&) [with T1 = double; T2 = double; T3 = double; T4 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 992 | rx = detail::ibeta_inv_imp( | ~~~~~~~~~~~~~~~~~~~~~^ 993 | static_cast(a), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 994 | static_cast(b), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 995 | static_cast(p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 996 | static_cast(1 - p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 997 | forwarding_policy(), &ry); | ~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:20: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(RT1, RT2, RT3, const Policy&) [with RT1 = double; RT2 = double; RT3 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 1023 | return ibeta_inv(a, b, p, static_cast(nullptr), pol); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:32: required from here 32 | return boost::math::ibeta_inv(a, b, p, boost_policy_t<>()); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable ‘x_extrema’ [-Wunused-variable] 29 | const T x_extrema = 1 / (1 + a); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 1>; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 2, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 2, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 2, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 2, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 2, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 2, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 203 | PanelType panel(m_arg, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:277: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 2, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 2, -1, true> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 100 | pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2256:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2256 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2258:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2258 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2259 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2298 | PacketBlock kernel_half; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2304 | PacketBlock kernel_quarter; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gebp_kernel::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, ResScalar, Index, Index, Index, Index) [with LhsScalar = double; RhsScalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 113 | gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | (std::min)(size,i2), alpha, -1, -1, 0, 0); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1920:103: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1920 | const int SResPacketHalfSize = unpacket_traits::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1921 | const int SResPacketQuarterSize = unpacket_traits::half>::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1977:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1977 | typedef typename conditional=8,typename unpacket_traits::half,SResPacket>::type SResPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1978:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1978 | typedef typename conditional=8,typename unpacket_traits::half,SLhsPacket>::type SLhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1979:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1979 | typedef typename conditional=8,typename unpacket_traits::half,SRhsPacket>::type SRhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1980:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1980 | typedef typename conditional=8,typename unpacket_traits::half,SAccPacket>::type SAccPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from ‘void Eigen::internal::tribb_kernel::operator()(ResScalar*, Index, Index, const LhsScalar*, const RhsScalar*, Index, Index, const ResScalar&) [with LhsScalar = double; RhsScalar = double; Index = long int; int mr = 4; int nr = 4; bool ConjLhs = false; bool ConjRhs = false; int ResInnerStride = 1; int UpLo = 2; ResScalar = double]’ 155 | Matrix buffer((internal::constructor_without_unaligned_array_assert())); | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:26: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:43: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:352:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 352 | Block A21(mat,k+1,k,rs,1); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:80: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:67: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, true>, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_linesearch.hpp:247:0: required from ‘int stan::optimization::WolfeLineSearch(FunctorType&, Scalar&, XType&, Scalar&, XType&, const XType&, const XType&, const Scalar&, const XType&, const Scalar&, const Scalar&, const Scalar&, const Scalar&, const Scalar&) [with FunctorType = ModelAdaptor; Scalar = double; XType = Eigen::Matrix]’ 247 | x1.noalias() = x0 + alpha1 * p; /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 209 | = WolfeLineSearch(_func, _alpha, _xk_1, _fk_1, _gk_1, _pk, _xk, _fk, 210 | _gk, _ls_opts.c1, _ls_opts.c2, _ls_opts.minAlpha, 211 | _ls_opts.maxLSIts, _ls_opts.maxLSRestarts); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from ‘void stan::optimization::BFGSUpdate_HInv::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 55 | pk.noalias() = -(_Hk * gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 254 | _qn.search_direction(_pk, _gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:537:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:537:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, 1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:783:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 783 | const auto& psi = stan::math::to_ref(psi_arg__); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::OuterStride<> > >::match, -1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, -1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, -1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:784:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 784 | const auto& phi_raw = stan::math::to_ref(phi_raw_arg__); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:785:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 785 | const auto& logit_p = stan::math::to_ref(logit_p_arg__); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:831:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:840:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Product >, Eigen::Matrix, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Product >, Eigen::Matrix, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Product >, Eigen::Matrix, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Product >, Eigen::Matrix, 1>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Product >, Eigen::Matrix, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:839:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from ‘Eigen::MapBase::ScalarWithConstIfNotLvalue& Eigen::MapBase::coeffRef(Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long int]’ 15 | EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 367 | matA.col(i).coeffRef(i+1) = 1; | ~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from ‘void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase&, Eigen::DenseBase&, const Eigen::JacobiRotation&) [with VectorX = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]’ 475 | EIGEN_PLAIN_ENUM_MIN(evaluator::Alignment, evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from ‘void Eigen::MatrixBase::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation&) [with OtherScalar = double; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’ 315 | internal::apply_rotation_in_the_plane(x, y, j.transpose()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:895:24: required from ‘void Eigen::internal::tridiagonal_qr_step(RealScalar*, RealScalar*, Index, Index, Scalar*, Index) [with int StorageOrder = 0; RealScalar = double; Scalar = double; Index = long int]’ 895 | q.applyOnTheRight(k,k+1,rot); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:548:87: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 548 | internal::tridiagonal_qr_step(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, -1, 1, false> >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::min_coeff_visitor, -1, 1, false>, 0>; Derived = Eigen::Block, -1, 1, false>]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:323:14: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 323 | this->visit(minVisitor); | ~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:496:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 496 | return minCoeff(index); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:35: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, true>, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:74: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:50: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, -1>&>(const Eigen::Matrix, -1, -1>&):: [with auto:12 = const Eigen::Matrix, -1, -1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:30:0: required from ‘auto stan::math::diag_pre_multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Matrix, -1, -1>; stan::require_vector_t* = 0; stan::require_matrix_t* = 0; stan::require_any_st_var* = 0]’ 30 | using ret_type = return_var_matrix_t; stanExports_colext.h:840:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:34:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:36:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:36:0: required from ‘auto stan::math::diag_pre_multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Matrix, -1, -1>; stan::require_vector_t* = 0; stan::require_matrix_t* = 0; stan::require_any_st_var* = 0]’ 36 | arena_m1.adj() += arena_m2.val().cwiseProduct(ret.adj()).rowwise().sum(); stanExports_colext.h:840:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:37:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:43:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:45:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:45:0: required from ‘auto stan::math::diag_pre_multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Matrix, -1, -1>; stan::require_vector_t* = 0; stan::require_matrix_t* = 0; stan::require_any_st_var* = 0]’ 45 | arena_m1.adj() += arena_m2.val().cwiseProduct(ret.adj()).rowwise().sum(); stanExports_colext.h:840:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:51:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/diag_pre_multiply.hpp:53:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 55 | using return_t stanExports_colext.h:839:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_colext.h:839:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, 1, -1>; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 36 | using return_t stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>&>(const Eigen::Matrix, 1, -1>&)::::, const Eigen::Matrix, 1, -1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>&>(const Eigen::Matrix, 1, -1>&)::::, const Eigen::Matrix, 1, -1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>&>(const Eigen::Matrix, 1, -1>&)::::, const Eigen::Matrix, 1, -1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1>&>(const Eigen::Matrix, 1, -1>&)::::, const Eigen::Matrix, 1, -1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1>&>(const Eigen::Matrix, 1, -1>&)::::, const Eigen::Matrix, 1, -1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, 1, -1>&>(const Eigen::Matrix, 1, -1>&):: [with auto:12 = const Eigen::Matrix, 1, -1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, 1, -1>; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 55 | using return_t stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&)::::, const Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&)::::, const Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&)::::, const Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&)::::, const Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&)::::, const Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, 1, -1>, void>&>(arena_matrix, 1, -1>, void>&):: [with auto:12 = stan::math::arena_matrix, 1, -1>, void>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, 1, -1>; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, -1, -1>, 1, -1, false>; T4__ = Eigen::Block, -1, -1>, -1, -1, false>; T5__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:438:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 438 | const auto& pars1 = stan::math::to_ref(pars1_arg__); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | = to_ref_if::value>(y_scaled * y_scaled); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from ‘stan::math::var stan::math::accumulator::type>::value, void>::type>::sum() const [with T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value; stan::math::var = stan::math::var_value]’ 135 | inline var sum() const { return stan::math::sum(buf_); } stanExports_colext.h:2588:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2588 | return lp_accum__.sum(); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false>, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1, 1, false>, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1, 1, false>, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1, 1, false>, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:672:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 672 | const auto& logit_p = stan::math::to_ref(logit_p_arg__); stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 453 | RealScalar scale = mat.cwiseAbs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:34:74: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:60: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, -1>&>(const Eigen::VectorBlock, -1>&):: [with auto:14 = const Eigen::VectorBlock, -1>]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_column_vector_or_scalar.hpp:60:54: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar > >(Eigen::Transpose >&&):: [with auto:14 = Eigen::Transpose >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv > > >(const Eigen::ArrayWrapper > >&):: [with auto:221 = Eigen::ArrayWrapper > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > > >(const Eigen::ArrayWrapper > >&):: [with auto:170 = Eigen::ArrayWrapper > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:98:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square > > >(const Eigen::ArrayWrapper > >&):: [with auto:239 = Eigen::ArrayWrapper > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::Array > >(const Eigen::CwiseUnaryOp, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseUnaryOp, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp >(const Eigen::Array&):: [with auto:216 = Eigen::Array]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:17: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log >(const Eigen::Array&):: [with auto:170 = Eigen::Array]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:27: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs >(const Eigen::Array&):: [with auto:10 = Eigen::Array]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&):: [with auto:12 = Eigen::ArrayWrapper, 1, -1> > >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv >(const Eigen::Array&):: [with auto:221 = Eigen::Array]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square >(const Eigen::Array&):: [with auto:239 = Eigen::Array]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, -1, false>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1, -1, false>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, -1, -1, false>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, -1, -1, false>, 1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_colext.h:702:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false>, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, -1, 1, false>, -1>&>(const Eigen::VectorBlock, -1, 1, false>, -1>&):: [with auto:14 = const Eigen::VectorBlock, -1, 1, false>, -1>]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from ‘stan::math::value_of_rec, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:2 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&):: [with auto:14 = const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::; Args = {const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:66:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:53: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:44: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:687:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 687 | stan::math::exp(stan::math::bernoulli_logit_lpmf(y, logit_p)), stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:76:18: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 76 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:687:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 687 | stan::math::exp(stan::math::bernoulli_logit_lpmf(y, logit_p)), stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_colext.h:687:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 687 | stan::math::exp(stan::math::bernoulli_logit_lpmf(y, logit_p)), stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_colext.h:687:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 687 | stan::math::exp(stan::math::bernoulli_logit_lpmf(y, logit_p)), stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Product, Eigen::Matrix, 0>; U = Eigen::Matrix; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Product, Eigen::Matrix, 0>; U = Eigen::Matrix; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, true>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, true>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, true>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 1, -1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 1, -1, true>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:54: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Block, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (2 / (1 + exp_y_minus_mu_div_sigma) - 1) * inv_sigma); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ^~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | const auto& exp_mu_div_sigma = to_ref(exp(mu_val * inv_sigma)); | ~~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, -1, 1, false> > >(const Eigen::ArrayWrapper, -1, 1, false> >&):: [with auto:170 = Eigen::ArrayWrapper, -1, 1, false> >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_colext.h:454:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_colext.h:465:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_colext.h:470:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > >(const Eigen::ArrayWrapper >&):: [with auto:170 = Eigen::ArrayWrapper >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, -1, 1, false>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1>, -1, 1, false>, -1, 1, false> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:687:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_colext.h:687:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_colext.h:687:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 16, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 16, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 16, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from ‘void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Func = generic_product_impl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]’ 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:333: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 306 | typedef typename Traits::LhsPacket LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = int; T_scale = double; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::CwiseUnaryView, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >; U = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; U = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::CwiseUnaryView, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >; U = Eigen::Map, 0, Eigen::Stride<0, 0> >; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 63 | check_finite(function, "Location parameter", mu_val); stanExports_colext.h:454:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 454 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_colext.h:454:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 454 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:83:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 83 | check_positive_finite(function, "Degrees of freedom parameter", nu_val); stanExports_colext.h:465:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 465 | stan::math::student_t_lpdf(x, pars1, pars2, pars3)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:45:15: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 45 | check_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 470 | out = (out + stan::math::logistic_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:475:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 475 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, 1, -1>; T_scale = Eigen::Matrix, 1, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_colext.h:454:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Matrix, 1, -1>; T3__ = Eigen::Matrix, 1, -1>; T4__ = Eigen::Matrix, 1, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 454 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan, -1, 1, false>, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false>, -1, 1, false> >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:54:16: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 54 | check_not_nan(function, "Logit transformed probability parameter", theta_val); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:687:0: required from ‘Eigen::Matrix::type>::type, -1, 1> model_colext_namespace::get_pY(const std::vector&, const T1__&, const int&, std::ostream*) [with T1__ = Eigen::VectorBlock, -1, 1, false>, -1>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 687 | stan::math::exp(stan::math::bernoulli_logit_lpmf(y, logit_p)), stanExports_colext.h:829:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 829 | get_pY( 830 | stan::model::rvalue(y, "y", stan::model::index_min_max(idx, end)), 831 | stan::model::rvalue(logit_p, "logit_p", 832 | stan::model::index_min_max(idx, end)), 833 | stan::model::rvalue(nd, "nd", 834 | stan::model::index_uni( 835 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)))), 836 | pstream__), "assigning variable Dpt"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false>, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Block, -1, 1, false>]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:45:15: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 45 | check_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 470 | out = (out + stan::math::logistic_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:475:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 475 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_colext.h:454:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 454 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:45:15: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 45 | check_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:470:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 470 | out = (out + stan::math::logistic_lpdf(x, pars1, pars2)); stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_colext.h:475:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 475 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:166:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from ‘static void Eigen::internal::generic_product_impl::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix; LhsT = Eigen::Matrix; RhsT = Eigen::Transpose >; Func = Eigen::internal::assign_op; Scalar = double; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); | ~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Array; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Array; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::Array; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:313: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h: In instantiation of ‘void Eigen::internal::BlockedInPlaceTranspose(MatrixType&) [with MatrixType = Eigen::Matrix; long int Alignment = 16]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:308:89: required from ‘static void Eigen::internal::inplace_transpose_selector::run(MatrixType&) [with MatrixType = Eigen::Matrix; bool MatchPacketSize = false]’ 308 | BlockedInPlaceTranspose::Alignment>(m); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:348:53: required from ‘void Eigen::DenseBase::transposeInPlace() [with Derived = Eigen::Matrix]’ 348 | internal::inplace_transpose_selector::run(derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:185:25: required from ‘Eigen::Matrix::type, -1, -1> stan::math::to_matrix(EigMat&&, int, int, bool) [with EigMat = const Eigen::Matrix&; stan::require_eigen_t* = 0; typename stan::value_type::type = double]’ 185 | res.transposeInPlace(); | ~~~~~~~~~~~~~~~~~~~~^~ stanExports_colext.h:711:0: required from ‘Eigen::Matrix::type>::type, -1, -1> model_colext_namespace::phi_matrix(const T0__&, std::ostream*) [with T0__ = Eigen::Block, -1, -1, false>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 711 | return stan::math::to_matrix(phi_raw, 2, 2, 0); stanExports_colext.h:744:0: required from ‘Eigen::Matrix::type>::type, -1, -1> model_colext_namespace::get_phi(const T0__&, const int&, const int&, std::ostream*) [with T0__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 744 | return phi_matrix( 745 | stan::model::rvalue(phi_raw, "phi_raw", 746 | stan::model::index_uni(Tstart), stan::model::index_omni()), 747 | pstream__); stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:272:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 272 | PacketBlock A; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:272:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:280:29: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 280 | PacketBlock B; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:280:29: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h: In instantiation of ‘void Eigen::internal::BlockedInPlaceTranspose(MatrixType&) [with MatrixType = Eigen::Matrix; long int Alignment = 0]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:310:56: required from ‘static void Eigen::internal::inplace_transpose_selector::run(MatrixType&) [with MatrixType = Eigen::Matrix; bool MatchPacketSize = false]’ 310 | BlockedInPlaceTranspose(m); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:348:53: required from ‘void Eigen::DenseBase::transposeInPlace() [with Derived = Eigen::Matrix]’ 348 | internal::inplace_transpose_selector::run(derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:185:25: required from ‘Eigen::Matrix::type, -1, -1> stan::math::to_matrix(EigMat&&, int, int, bool) [with EigMat = const Eigen::Matrix&; stan::require_eigen_t* = 0; typename stan::value_type::type = double]’ 185 | res.transposeInPlace(); | ~~~~~~~~~~~~~~~~~~~~^~ stanExports_colext.h:711:0: required from ‘Eigen::Matrix::type>::type, -1, -1> model_colext_namespace::phi_matrix(const T0__&, std::ostream*) [with T0__ = Eigen::Block, -1, -1, false>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 711 | return stan::math::to_matrix(phi_raw, 2, 2, 0); stanExports_colext.h:744:0: required from ‘Eigen::Matrix::type>::type, -1, -1> model_colext_namespace::get_phi(const T0__&, const int&, const int&, std::ostream*) [with T0__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 744 | return phi_matrix( 745 | stan::model::rvalue(phi_raw, "phi_raw", 746 | stan::model::index_uni(Tstart), stan::model::index_omni()), 747 | pstream__); stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:272:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 272 | PacketBlock A; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:272:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:280:29: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 280 | PacketBlock B; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:280:29: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Product, Eigen::Matrix, 0>; U = Eigen::Matrix; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 2, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:40: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; Dest = Eigen::Block, -1, 1, false>; typename Dest::Scalar = double]’ 296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; Rhs = Eigen::Transpose >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:534:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_colext_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 534 | lp_single_prior( 535 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 536 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 537 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 538 | stan::model::index_min_max(1, 1)), 539 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 540 | stan::model::index_min_max(1, 1)), 541 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 542 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:642:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 642 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/broadcast_array.hpp:32:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:647:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 647 | stan::math::normal_lpdf( 648 | stan::model::rvalue(b, "b", 649 | stan::model::index_min_max(idx, 650 | ((stan::model::rvalue(n_random, "n_random", 651 | stan::model::index_uni(i)) + idx) - 1))), 0, 652 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:292:8: required from ‘struct Eigen::internal::evaluator > >’ 292 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_colext.h:2758:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2758 | stan::math::csr_matrix_times_vector( 2759 | stan::model::rvalue(Zdim_state, "Zdim_state", 2760 | stan::model::index_uni(1)), 2761 | stan::model::rvalue(Zdim_state, "Zdim_state", 2762 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2763 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:31: /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: required from ‘bool boost::range::equal(const SinglePassRange1&, const SinglePassRange2&) [with SinglePassRange1 = boost::iterator_range<__gnu_cxx::__normal_iterator > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/iterator_range_core.hpp:644:32: required from ‘bool boost::operator==(const iterator_range&, const iterator_range&) [with Iterator1T = __gnu_cxx::__normal_iterator >; Iterator2T = __gnu_cxx::__normal_iterator >]’ 644 | return boost::equal( l, r ); | ~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from ‘bool boost::algorithm::split_iterator::equal(const boost::algorithm::split_iterator&) const [with IteratorT = __gnu_cxx::__normal_iterator >]’ 359 | m_Match==Other.m_Match && /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:649:26: required from ‘static bool boost::iterators::iterator_core_access::equal(const Facade1&, const Facade2&, mpl_::true_) [with Facade1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; mpl_::true_ = mpl_::bool_]’ 649 | return f1.equal(f2); | ~~~~~~~~^~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator==(const iterator_facade&, const iterator_facade&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference1 = long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:337: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 62 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 63 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2540:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2540 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 2541 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_colext.h:475:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_colext.h:481:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:2552:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 2552 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 2553 | b_state, n_random_state, sigma_state, 2554 | stan::model::rvalue(prior_dist_state, 2555 | "prior_dist_state", stan::model::index_uni(3)), 2556 | prior_pars_state, pstream__)); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, false>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:81:75: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 81 | gemm_pack_rhs pack_rhs; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::CopyConstructible::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 167 | BOOST_CONCEPT_USAGE(CopyConstructible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::IncrementableIteratorConcept::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 136 | BOOST_CONCEPT_USAGE(IncrementableIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::EqualityComparable::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 233 | BOOST_CONCEPT_USAGE(EqualityComparable) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:166: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h: In instantiation of ‘Index Eigen::internal::first_default_aligned(const Scalar*, Index) [with Scalar = double; Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’ 89 | Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 500 | return first_aligned::alignment>(array, size); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:169:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheRight(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 169 | this->col(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:304:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 131 | this->row(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 132 | bottom.noalias() -= tau * essential * tmp; | ~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:184:17: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 184 | pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 1; bool ConjugateLhs = false; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 346 | pack_rhs_panel(blockB+j2*actual_kc, | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ 347 | rhs.getSubMapper(actual_k2+panelOffset, actual_j2), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 348 | panelLength, actualPanelWidth, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | actual_kc, panelOffset); | ~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]’ 783 | triangular_product_impl::run(dst, lhs, rhs.nestedExpression(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 2>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 2>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 2>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, 1>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, 1>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, 1>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 5>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, true>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 233 | gemm_pack_rhs pack_rhs_panel; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Matrix; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Matrix]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from ‘void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >; Func = generic_product_impl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]’ 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:42: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:57: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:73:50: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Transpose, -1, -1, false>, 1, -1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; ExpressionType = Eigen::Block, -1, -1, false>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 319 | pack_lhs_panel(blockA, lhs.getSubMapper(i2,absolute_j2), | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 320 | actualPanelWidth, actual_mc, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 321 | actual_kc, j2); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 150 | Matrix triangularBuffer(a); | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 153 | triangularBuffer.diagonal().setZero(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from ‘ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]’ 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:444:18: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:282:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >’ 282 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Derived = Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_colext.h:2440:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2440 | stan::math::csr_matrix_times_vector( 2441 | stan::model::rvalue(Zdim_state, "Zdim_state", 2442 | stan::model::index_uni(1)), 2443 | stan::model::rvalue(Zdim_state, "Zdim_state", 2444 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 2445 | b_state)), "assigning variable logit_psi"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:660:61: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:660:61: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; Dest = Eigen::Block, -1, 1, true>; typename Dest::Scalar = double]’ 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = false; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Matrix; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from ‘void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, Eigen::Transpose >, 1> >; Functor = Eigen::internal::assign_op; int Version = 1; Eigen::Index = long int]’ 654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col)); | ~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Derived = Eigen::Block, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from ‘Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, false>; Scalar = double]’ 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::OuterStride<> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:39:18: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:57: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:43: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]’ 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 1>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 1>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense >, Eigen::Matrix, 1>, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl >, Eigen::Matrix, 1>, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, Eigen::Matrix, 1>, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Product >, Eigen::Matrix, 1>; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Product >, Eigen::Matrix, 1>]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Product >, Eigen::Matrix, 1>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:42: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Product >, Eigen::Matrix, 1>, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Product >, Eigen::Matrix, 1>, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Product >, Eigen::Matrix, 1>, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Product >, Eigen::Matrix, 1>, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Product >, Eigen::Matrix, 1>, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Product >, Eigen::Matrix, 1>, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:301:29: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = false; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Matrix, 1>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, Eigen::Matrix, 1> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Product >, Eigen::Matrix, 1>; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = false; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_colext.h:2433:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2433 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:43: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]’ 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Transpose >; typename Dest::Scalar = double]’ 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 1> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 1> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense >, Eigen::Matrix, 1> >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl >, Eigen::Matrix, 1> >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >, Eigen::Matrix, 1> >; Rhs = Eigen::Transpose, 1, -1, false> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]’ 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block, -1, -1, false>; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; int Side = 1; int Mode = 2]’ 71 | triangular_solve_vector | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:816:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | get_phi(phi_raw, 817 | stan::model::rvalue(Tsamp, "Tsamp", stan::model::index_uni(t)), 818 | stan::model::rvalue(Tsamp, "Tsamp", 819 | stan::model::index_uni((t + 1))), pstream__), stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:32: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]’ 194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, 1, false>]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_colext_namespace::model_colext; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_colext_namespace::model_colext]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_colext.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/access_helpers.hpp:92:0: required from ‘void stan::model::internal::assign_impl(T1&&, T2&&, const char*) [with T1 = Eigen::Matrix&; T2 = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_all_eigen_t* = 0]’ 92 | x = std::forward(y); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from ‘void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]’ 60 | internal::assign_impl(x, std::forward(y), name); stanExports_colext.h:2750:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2750 | stan::model::assign(logit_psi, 2751 | stan::math::add(stan::math::multiply(X_state, beta_state), 2752 | offset_state), "assigning variable logit_psi"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, Eigen::Matrix, 1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, Eigen::Matrix, 1> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block >, Eigen::Matrix, 1> >, 1, -1, true>, const Eigen::Transpose, 1, -1, false> > > >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 341 | dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false> >, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false> >, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Product >, Eigen::Matrix, 1>; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Product >, Eigen::Matrix, 1>; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:838:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 838 | stan::model::assign(phi_prod, 839 | stan::math::multiply(stan::model::deep_copy(phi_prod), 840 | stan::math::diag_pre_multiply(Dpt, phi)), 841 | "assigning variable phi_prod"); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::InnerStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::InnerStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::InnerStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:106: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from ‘void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >; Functor = Eigen::internal::assign_op; int Version = 1; Eigen::Index = long int]’ 654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col)); | ~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix, -1, -1>; T6__ = Eigen::Matrix, -1, -1>; T7__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2536:0: required from ‘stan::scalar_type_t model_colext_namespace::model_colext::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 2536 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2537 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3635:0: required from ‘T_ model_colext_namespace::model_colext::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 3635 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_colext_namespace::model_colext; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_colext.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block, -1, -1, false>, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_colext.h:867:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_colext_namespace::lp_colext(const std::vector&, const std::vector&, const std::vector&, const T3__&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T3__ = Eigen::Block, 1, -1, false>; T4__ = Eigen::Block, -1, -1, false>; T5__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 867 | stan::math::dot_product(stan::math::multiply(psi, phi_prod), Dpt)); stanExports_colext.h:910:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_colext_namespace::get_loglik_colext(const std::vector&, const int&, const std::vector&, const std::vector >&, const std::vector >&, const T5__&, const T6__&, const T7__&, const std::vector >&, std::ostream*) [with T5__ = Eigen::Matrix; T6__ = Eigen::Matrix; T7__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 910 | lp_colext( 911 | stan::model::rvalue(y, "y", 912 | stan::model::index_min_max( 913 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 914 | stan::model::index_uni(1)), 915 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 916 | stan::model::index_uni(2)))), 917 | stan::model::rvalue(Tsamp, "Tsamp", 918 | stan::model::index_min_max( 919 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 920 | stan::model::index_uni(3)), 921 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 922 | stan::model::index_uni(4)))), 923 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 924 | stan::model::index_omni()), 925 | stan::model::rvalue(psi_raw, "psi_raw", stan::model::index_uni(i), 926 | stan::model::index_omni()), 927 | stan::model::rvalue(phi_raw, "phi_raw", 928 | stan::model::index_min_max( 929 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 930 | stan::model::index_uni(5)), 931 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 932 | stan::model::index_uni(6))), stan::model::index_omni()), 933 | stan::model::rvalue(logit_p, "logit_p", 934 | stan::model::index_min_max( 935 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 936 | stan::model::index_uni(1)), 937 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 938 | stan::model::index_uni(2)))), 939 | stan::model::rvalue(nd, "nd", stan::model::index_uni(i), 940 | stan::model::index_omni()), pstream__), "assigning variable out", stanExports_colext.h:2854:0: required from ‘void model_colext_namespace::model_colext::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 2854 | get_loglik_colext(y, M, Tsamp, J, si, psi_raw, phi_raw, logit_p, 2855 | no_detects, pstream__), "assigning variable log_lik"); stanExports_colext.h:3624:0: required from ‘void model_colext_namespace::model_colext::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 3624 | write_array_impl(base_rng, params_r, params_i, vars, 3625 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_colext_namespace::model_colext; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_colext.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 327 | internal::triangular_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 328 | | ~~~~~~~~~ 332 | ::run(actualLhs.rows(),actualLhs.cols(), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 333 | actualLhs.data(),actualLhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 334 | actualRhsPtr,1, | ~~~~~~~~~~~~~~~ 335 | dest.data(),dest.innerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 336 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:27: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::sum > >(const std::vector, arena_allocator > >&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl, 0, Eigen::Stride<0, 0> >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:883:17: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = add_assign_op]’ 883 | ActualDstType actualDst(dst); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:194:18: required from ‘Derived& Eigen::ArrayBase::operator+=(const Eigen::ArrayBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Derived = Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >]’ 194 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:883:17: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = add_assign_op]’ 883 | ActualDstType actualDst(dst); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:194:18: required from ‘Derived& Eigen::ArrayBase::operator+=(const Eigen::ArrayBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Derived = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >]’ 194 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::dot_product, 1, -1>, Eigen::Matrix, -1, 1> >(const Eigen::Matrix, 1, -1>&, const Eigen::Matrix, -1, 1>&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_colext_namespace::model_colext; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c stanExports_single_season.cc -o stanExports_single_season.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:3, from stanExports_single_season.h:23, from stanExports_single_season.cc:5: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:18, from /usr/local/lib/R/library/BH/include/boost/shared_ptr.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/time_clock.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:15, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:4: /usr/local/lib/R/library/BH/include/boost/smart_ptr/detail/shared_count.hpp:361:33: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 361 | explicit shared_count( std::auto_ptr & r ): pi_( new sp_counted_impl_p( r.get() ) ) | ^~~~~~~~ In file included from /usr/include/c++/14/memory:78, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:7: /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:251:65: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 251 | template< class T, class R > struct sp_enable_if_auto_ptr< std::auto_ptr< T >, R > | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:508:31: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 508 | explicit shared_ptr( std::auto_ptr & r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:521:22: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 521 | shared_ptr( std::auto_ptr && r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:604:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 604 | shared_ptr & operator=( std::auto_ptr & r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:613:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 613 | shared_ptr & operator=( std::auto_ptr && r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function ‘boost::shared_ptr& boost::shared_ptr::operator=(std::auto_ptr<_Up>&&)’: /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:615:38: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 615 | this_type( static_cast< std::auto_ptr && >( r ) ).swap( *this ); | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from ‘struct Eigen::internal::traits > >’ 19 | template struct traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from ‘class Eigen::SolverBase > >’ 68 | class SolverBase : public EigenBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from ‘class Eigen::LDLT >’ 59 | template class LDLT | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from ‘class Eigen::LDLT >’ 69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from ‘class Eigen::LDLT >’ 287 | TmpMatrixType m_temporary; | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:29: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:41: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:45: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:26: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:34: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_array.hpp:37:49: required from here 37 | Eigen::VectorXd v = Eigen::VectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:28: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:39: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:53: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:72: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:77: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:17: required from here 71 | A.diagonal().array() -= mu; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:29: required from here 71 | A.diagonal().array() -= mu; | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:22: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:38: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:178:58: required from here 178 | alpha = Eigen::VectorXd::Constant(_p_max - 1, normA); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::internal::member_minCoeff, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::internal::member_minCoeff, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::internal::member_minCoeff, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, Eigen::internal::member_minCoeff, 0>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:203:38: required from here 203 | int cost = c.colwise().minCoeff().minCoeff(&m); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/one_hot_row_vector.hpp:25:52: required from here 25 | Eigen::RowVectorXd ret = Eigen::RowVectorXd::Zero(K); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:13:64: required from here 13 | : m_(Eigen::VectorXd::Zero(n)), m2_(Eigen::MatrixXd::Zero(n, n)) { | ~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:26:31: required from here 26 | Eigen::VectorXd delta(q - m_); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:38: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:37:40: required from here 37 | covar = m2_ / (num_samples_ - 1.0); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_var_estimator.hpp:28:30: required from here 28 | m2_ += delta.cwiseProduct(q - m_); | ~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here 77 | Eigen::Map(dz_dt.data(), dz_dt.size()) = f_y_t; | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:13, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:43: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combination(std::vector&, const int&, const int&, const int&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:73:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 73 | for (std::size_t i = 0; i < p - 1; i++) { | ~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:79:16: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 79 | } while (k < x); | ~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:102:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 102 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:105:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 105 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::increment(std::vector&, const int&, const double&, const std::vector&, std::vector&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:126:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 126 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 132 | while ((first_zero < index.size()) && index[first_zero]) { | ~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 135 | if (first_zero == index.size()) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:143:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 143 | for (std::size_t i = 0; i != first_zero + 1; i++) { | ~~^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:168:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 168 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here 40 | coupled_state.size()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/mpl/aux_/na_assert.hpp:23, from /usr/local/lib/R/library/BH/include/boost/mpl/arg.hpp:25, from /usr/local/lib/R/library/BH/include/boost/mpl/placeholders.hpp:24, from /usr/local/lib/R/library/BH/include/boost/mpl/apply.hpp:24, from /usr/local/lib/R/library/BH/include/boost/serialization/array_optimization.hpp:18, from /usr/local/lib/R/library/BH/include/boost/serialization/array_wrapper.hpp:21, from /usr/local/lib/R/library/BH/include/boost/serialization/array.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:22, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/vector.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint.hpp:25, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:16: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp: At global scope: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: warning: unnecessary parentheses in declaration of ‘assert_arg’ [-Wparentheses] 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ | - 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ | - /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of ‘assert_not_arg’ [-Wparentheses] 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | - 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ | - In file included from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/traits.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:27: /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:111:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 111 | public std::iterator { | ^~~~~~~~ In file included from /usr/include/c++/14/bits/stl_algobase.h:65, from /usr/include/c++/14/bits/specfun.h:43, from /usr/include/c++/14/cmath:3898, from /usr/local/lib/R/library/Rcpp/include/Rcpp/platform/compiler.h:100, from /usr/local/lib/R/library/Rcpp/include/Rcpp/r/headers.h:66, from /usr/local/lib/R/library/Rcpp/include/RcppCommon.h:30, from /usr/local/lib/R/library/Rcpp/include/Rcpp.h:27, from stanExports_single_season.cc:3: /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:149:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 149 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:204:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 204 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/invoke.hpp:52, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/adapter/fused.hpp:17, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/generation/make_fused.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/include/make_fused.hpp:11, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:28, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33: /usr/local/lib/R/library/BH/include/boost/get_pointer.hpp:48:40: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 48 | template T * get_pointer(std::auto_ptr const& p) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:38:59: required from here 38 | Eigen::VectorXd stddev = S_ldlt.vectorD().array().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 5>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:75: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:76: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:135:41: required from here 135 | Eigen::VectorXd(F.transpose() * theta_t), V_ldlt, rng); | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_hidden_state_prob.hpp:77:52: required from here 77 | alphas.col(n) = alphas.col(n).cwiseProduct(beta); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_latent_rng.hpp:71:73: required from here 71 | probs_vec = alphas.col(n_transitions) / alphas.col(n_transitions).sum(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::TriangularView >, 2>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::TriangularView >, 2>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::TriangularView >, 2>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:42: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::TriangularView >, 2>, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:25:32: required from here 25 | S_inv = ldlt_of_S.solve(S_inv); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:47: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:54: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:109:64: required from here 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Matrix >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: recursively required by substitution of ‘template const Eigen::internal::triangular_solve_retval >, 6>, Other> Eigen::TriangularViewImpl >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase&) const [with int Side = ; Other = ]’ 108 | * (D_ldlt.matrixU().solve( | ~~~~~~~~~~~~~~~~~~~~~~^ 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from ‘struct Eigen::internal::accessors_level >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 32 | enum { has_direct_access = (traits::Flags & DirectAccessBit) ? 1 : 0, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:43: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:51: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:52: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/multinomial_logit_lpmf.hpp:39:0: required from here 39 | lp += lgamma(1 + ns_map.sum()) - lgamma(1 + ns_map).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_ccdf_log.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob.hpp:240, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:16: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp: In function ‘stan::return_type_t stan::math::normal_lccdf(const T_y&, const T_loc&, const T_scale&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: ‘-Wmisleading-indentation’ is disabled from this point onwards, since column-tracking was disabled due to the size of the code/headers 68 | } else if (scaled_diff > 8.25 * INV_SQRT_TWO) { /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: adding ‘-flarge-source-files’ will allow for more column-tracking support, at the expense of compilation time and memory /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp: In member function ‘virtual std::vector > stan::io::dump::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 694 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 707 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here 102 | if (C_adj.size() > 0) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here 111 | = D_adj.adjoint().template triangularView(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1, -1, false>, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here 116 | D_adj.diagonal() *= 0.5; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from ‘class Eigen::RefBase, 0, Eigen::OuterStride<> > >’ 59 | template class RefBase | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from ‘class Eigen::Ref, 0, Eigen::OuterStride<> >’ 281 | template class Ref | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from ‘class Eigen::LLT, 0, Eigen::OuterStride<> >, 1>’ 76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:142:0: required from here 142 | check_pos_definite("cholesky_decompose", "m", L_factor); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here 144 | L_A.template triangularView().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_factor_constrain.hpp:42:0: required from here 42 | y_val.row(m).head(m) = x.val().segment(pos, m); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of ‘template static std::true_type stan::is_base_pointer_convertible >::f(const Eigen::EigenBase*) [with OtherDerived = ]’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible >’ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from ‘struct stan::is_eigen >’ 21 | : bool_constant::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of ‘template class stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix]’ 301 | (is_eigen::value || is_kernel_expression_and_not_scalar::value) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 1>’ 148 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 222 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from ‘class stan::math::arena_matrix, void>’ 129 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from ‘class stan::math::vari_value, void>’ 814 | using InnerIterator = typename arena_matrix::InnerIterator; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from ‘const auto& stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 419 | inline const auto& val() const noexcept { return vi_->val(); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from ‘class Eigen::Tridiagonalization >’ 97 | >::type SubDiagonalReturnType; | ^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from ‘class Eigen::SelfAdjointEigenSolver >’ 111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here 40 | arena_t eigenvals = solver.eigenvalues(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here 27 | g = x.adj(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0> > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:51:0: required from here 51 | reverse_pass_callback([arena_M, log_det, arena_M_inv_transpose]() mutable { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:73:0: required from here 73 | vector_d diff = (x_d.array() - x_d.maxCoeff()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here 81 | Eigen::Map(softmax_x_d_array, a_size) = softmax_x_d.array() / sum; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:50:0: required from here 50 | arena_powers[0] = Eigen::MatrixXd::Identity(N, N); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:53:0: required from here 53 | arena_powers[i] = arena_powers[1] * arena_powers[i - 1]; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:63:0: required from here 63 | adj_M += adj_C * arena_powers[i - 1].transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here 67 | Eigen::Map(variRefB_, M_, N_).adj() += adjB; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from here 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:55:0: required from here 55 | L.col(0).tail(pull) = CPCs.val().head(pull); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:56:0: required from here 56 | arena_acc.tail(pull) = 1.0 - CPCs.val().head(pull).array().square(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:63:0: required from here 63 | L.col(i).tail(pull) = cpc_seg * arena_acc.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_cov_matrix.hpp:56:0: required from here 56 | sds.adj() += (prod.adj().cwiseProduct(corr_L.val())).rowwise().sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/rows_dot_self.hpp:41:0: required from here 41 | x.adj() += (2 * res.adj()).asDiagonal() * x.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0, Eigen::Stride<0, 0> >, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here 56 | arena_Fp.diagonal().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here 70 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from ‘struct Eigen::internal::traits, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 278 | typedef typename DiagonalVectorType::Scalar Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from ‘class Eigen::DiagonalBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 18 | class DiagonalBase : public EigenBase | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from ‘class Eigen::DiagonalWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 293 | class DiagonalWrapper | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:63:0: required from here 63 | + arena_U * arena_D.asDiagonal().inverse() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here 80 | v1_map.adj() += di; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:23:0: required from here 23 | vector_d dtrs_vals = dtrs_map.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::val_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here 26 | fx = fx_var.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&):: [with auto:12 = const Eigen::Matrix, -1, 1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::; Args = {const Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from ‘auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]’ 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/algebra_solver_fp.hpp:101:0: required from here 101 | y_dummy(stan::math::value_of(y)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here 604 | f_y_t_vars.adj() = -Eigen::Map(NV_DATA_S(yB), N_); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/finite_diff_hessian_times_vector_auto.hpp:62:0: required from here 62 | hvp = (grad_forward - grad_backward) / (2 * epsilon); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/initialize.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:49: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function ‘virtual std::vector > stan::io::random_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 111 | for (comp_iter = 0, real_iter = 0; real_iter < val_r.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:182:0: required from here 182 | return normal_fullrank(Eigen::VectorXd(mu_.array().square()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:183:0: required from here 183 | Eigen::MatrixXd(L_chol_.array().square())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:197:0: required from here 197 | return normal_fullrank(Eigen::VectorXd(mu_.array().sqrt()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:198:0: required from here 198 | Eigen::MatrixXd(L_chol_.array().sqrt())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:263:0: required from here 263 | L_chol_.array() /= rhs.L_chol().array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:459:0: required from here 459 | L_grad.diagonal().array() += L_chol_.diagonal().array().inverse(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:370:0: required from here 370 | omega_grad.array() += tmp_mu_grad.array().cwiseProduct(eta.array()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:388:0: required from here 388 | omega_grad.array() = omega_grad.array().cwiseProduct(omega_.array().exp()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/nuts/base_nuts.hpp:175:0: required from here 175 | rho = rho_bck + rho_fwd; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 2>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 2>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 2>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 2>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 2>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:53:0: required from here 53 | z.p = z.inv_e_metric_.llt().matrixU().solve(u); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from ‘auto stan::math::to_matrix(const std::vector&, int, int) [with T = double]’ 133 | return Eigen::Map>( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 134 | &x[0], m, n); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/read_dense_inv_metric.hpp:33:0: required from here 33 | inv_metric = stan::math::to_matrix(dense_vals, num_params, num_params); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here 27 | covar = (n / (n + 5.0)) * covar /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of ‘template typename Eigen::ScalarBinaryOpTraits::Scalar, Eigen::internal::scalar_product_op::Scalar> >::ReturnType Eigen::MatrixBase >::dot(const Eigen::MatrixBase&) const [with OtherDerived = ]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here 27 | var = (n / (n + 5.0)) * var /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:68: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function ‘virtual std::vector > stan::io::array_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 304 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 317 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue_varmat.hpp:145:0: required from here 145 | x_ret_vals.coeffRef(j) = x.val().coeff(row_idx_val, col_idx_vals[j]); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_header.hpp:11, from stanExports_single_season.h:25: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp: At global scope: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:159: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(std::vector, std::allocator > >&, std::vector&, std::ostream*) const [with M = model_single_season_namespace::model_single_season; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 159 | inline math::var log_prob(std::vector& theta, stanExports_single_season.h:4104: note: by ‘model_single_season_namespace::model_single_season::log_prob’ 4104 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:154: warning: ‘double stan::model::model_base_crtp::log_prob(std::vector&, std::vector&, std::ostream*) const [with M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 154 | inline double log_prob(std::vector& theta, std::vector& theta_i, stanExports_single_season.h:4104: note: by ‘model_single_season_namespace::model_single_season::log_prob’ 4104 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:96: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(Eigen::Matrix, -1, 1>&, std::ostream*) const [with M = model_single_season_namespace::model_single_season; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 96 | inline math::var log_prob(Eigen::Matrix& theta, stanExports_single_season.h:4104: note: by ‘model_single_season_namespace::model_single_season::log_prob’ 4104 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:91: warning: ‘double stan::model::model_base_crtp::log_prob(Eigen::VectorXd&, std::ostream*) const [with M = model_single_season_namespace::model_single_season; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 91 | inline double log_prob(Eigen::VectorXd& theta, stanExports_single_season.h:4104: note: by ‘model_single_season_namespace::model_single_season::log_prob’ 4104 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:102:18: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0; stan::return_type_t = double]’ 102 | x.unaryExpr([lb, &lp](auto&& xx) { return lb_constrain(xx, lb, lp); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3462:0: required from here 3461 | sigma_state = in__.template read_constrain_lb< 3462 | Eigen::Matrix, jacobian__>(0, 3463 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:83:26: required from ‘auto stan::math::lb_constrain(T&&, L&&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = const int&; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 83 | return eval(x.unaryExpr([lb](auto&& x) { return lb_constrain(x, lb); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:388:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 388 | return stan::math::lb_constrain(this->read(sizes...), lb); stanExports_single_season.h:3462:0: required from here 3461 | sigma_state = in__.template read_constrain_lb< 3462 | Eigen::Matrix, jacobian__>(0, 3463 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from ‘auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]’ 107 | return m1 * m2; | ~~~^~~~ stanExports_single_season.h:3509:0: required from here 3509 | stan::math::add(stan::math::multiply(X_state, beta_state), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Mat2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_single_season.h:3509:0: required from here 3509 | stan::math::add(stan::math::multiply(X_state, beta_state), 3510 | offset_state), "assigning variable lp_state"); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from ‘struct Eigen::internal::traits >’ 17 | struct traits > : traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar&>(const std::vector&)::; Args = {const std::vector >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:72:21: required from ‘auto stan::math::as_array_or_scalar(T&&) [with T = const std::vector&; stan::require_std_vector_t* = 0; stan::require_not_std_vector_t::type>* = 0]’ 72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | std::forward(v)); | ~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:39: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:43: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:55: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&):: [with auto:10 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&)::; T2 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_t::type> >* = 0; T = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from ‘auto stan::math::fabs(const Container&) [with Container = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_container_st* = 0]’ 66 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:37: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&)::; T2 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_t::type> >* = 0; T = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:49:25: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk)); | ~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:22: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long unsigned int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here 97 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { stanExports_single_season.h: In instantiation of ‘void model_single_season_namespace::model_single_season::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = std::vector; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_single_season.h:4132:0: required from here 4132 | unconstrain_array_impl(params_constrained, params_i, 4133 | params_unconstrained, pstream); stanExports_single_season.h:3640: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 3640 | int pos__ = std::numeric_limits::min(); stanExports_single_season.h: In instantiation of ‘void model_single_season_namespace::model_single_season::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = Eigen::Matrix; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_single_season.h:4142:0: required from here 4142 | unconstrain_array_impl(params_constrained, params_i, 4143 | params_unconstrained, pstream); stanExports_single_season.h:3640: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 3640 | int pos__ = std::numeric_limits::min(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp: In instantiation of ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’: stanExports_single_season.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1252: warning: variable ‘ret’ set but not used [-Wunused-but-set-variable] 1252 | int ret = stan::services::error_codes::CONFIG; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 182 | Eigen::Matrix b_args(1); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:117:39: required from ‘TupleT stan::math::internal::grad_2F1_impl_ab(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 117 | inner_diff = g_current.array().abs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:204:78: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 204 | grad_tuple_ab = grad_2F1_impl_ab( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 205 | a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:12: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:47:0: required from here 47 | stan::math::check_not_nan(function, "Mean vector", mu); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:74:0: required from here 74 | stan::math::check_not_nan(function, "Cholesky factor", L_chol); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 207 | for (size_t i = 0; i < x.rows(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 208 | for (size_t j = 0; j < x.cols(); j++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:21:0: required from here 21 | stan::math::check_finite("check_finite", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:22:0: required from here 22 | stan::math::check_positive("check_positive", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here 30 | if (!var.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta.hpp:70, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:10: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp: In instantiation of ‘void stan::math::check_less_or_equal(const char*, const char*, const T_y&, const T_high&, Idxs ...) [with T_y = long unsigned int; T_high = long int; stan::require_all_stan_scalar_t* = 0; Idxs = {}]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’ 79 | stan::math::check_less_or_equal("validate_dims", "array_var_context", 80 | elem_dims_total[dims.size()], array_size); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp:39:20: warning: comparison of integer expressions of different signedness: ‘const long unsigned int’ and ‘const long int’ [-Wsign-compare] 39 | if (unlikely(!(y <= high))) { | ~~~^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/compiler_attributes.hpp:9:41: note: in definition of macro ‘unlikely’ 9 | #define unlikely(x) __builtin_expect(!!(x), 0) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:21: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_single_season.h:3842:0: required from ‘void model_single_season_namespace::model_single_season::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3842 | out__.write_free_lb(0, sigma_state); stanExports_single_season.h:4123:0: required from here 4123 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:32: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_single_season.h:3842:0: required from ‘void model_single_season_namespace::model_single_season::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3842 | out__.write_free_lb(0, sigma_state); stanExports_single_season.h:4123:0: required from here 4123 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_single_season.h:3842:0: required from ‘void model_single_season_namespace::model_single_season::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3842 | out__.write_free_lb(0, sigma_state); stanExports_single_season.h:4123:0: required from here 4123 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_single_season.h:3842:0: required from ‘void model_single_season_namespace::model_single_season::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3842 | out__.write_free_lb(0, sigma_state); stanExports_single_season.h:4123:0: required from here 4123 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_single_season.h:3842:0: required from ‘void model_single_season_namespace::model_single_season::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 3842 | out__.write_free_lb(0, sigma_state); stanExports_single_season.h:4123:0: required from here 4123 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp: In instantiation of ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; Eigen::MatrixXd = Eigen::Matrix]’: /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_single_season.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: ‘std::vector >::size_type’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 55 | if (p_names.size() != draws.cols()) { /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:71: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 71 | for (size_t i = 0; i < draws.rows(); ++i) { In file included from /usr/local/lib/R/library/BH/include/boost/concept/assert.hpp:35, from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:19, from /usr/local/lib/R/library/BH/include/boost/range/size_type.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/size.hpp:21, from /usr/local/lib/R/library/BH/include/boost/range/functions.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range.hpp:18, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:22: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept >, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:26, from /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:16, from /usr/local/lib/R/library/BH/include/boost/algorithm/string.hpp:23, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:46: /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::token_finderF >; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:98:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FormatterConcept >, boost::algorithm::detail::first_finderF, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:103:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function ‘void boost::algorithm::FormatterConcept::constraints() [with FormatterT = boost::algorithm::detail::const_formatF >; FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 65 | void constraints() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:19: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:330: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 72 | typedef blas_data_mapper ResMapper; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 451 | subdiag = mat.template diagonal<-1>().real(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 1, -1, false>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 191 | _pk.noalias() = -_gk; /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:192:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 192 | auto exp_x = to_arena(arena_x.val().array().exp()); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:193:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 193 | arena_t ret = exp_x + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&):: [with auto:12 = const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_single_season.h:3233:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3232 | sigma_state = in__.template read_constrain_lb< 3233 | Eigen::Matrix, jacobian__>(0, 3234 | lp__, n_group_vars_state); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:34:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 34 | auto arena_A_val = to_arena(arena_A.val()); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 36 | using return_t stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 47 | arena_A.adj() += res_adj * arena_B_val.transpose(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&):: [with auto:12 = stan::math::arena_matrix, -1, -1>, void>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 66 | = return_var_matrix_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:14 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), 3266 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:255:7: required from ‘class Eigen::Map >’ 255 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> >&>(arena_matrix, -1, 1> >&):: [with auto:12 = stan::math::arena_matrix, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:128:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 128 | arena_t res = w_val_mat * value_of(b_arena); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:135:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 135 | arena_t res = w_mat_arena.val() * b_arena; stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 114 | using ret_type = return_var_matrix_t; stanExports_single_season.h:3275:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3275 | stan::math::add(stan::model::deep_copy(lp_state), 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_single_season.h:3275:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3275 | stan::math::add(stan::model::deep_copy(lp_state), 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_single_season.h:3520:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3520 | stan::math::csr_matrix_times_vector( 3521 | stan::model::rvalue(Zdim_state, "Zdim_state", 3522 | stan::model::index_uni(1)), 3523 | stan::model::rvalue(Zdim_state, "Zdim_state", 3524 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3525 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from ‘auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Matrix&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]’ 187 | return v.segment(slice_start, slice_size); stanExports_single_season.h:849:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from ‘auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Map, 0, Eigen::Stride<0, 0> >&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]’ 187 | return v.segment(slice_start, slice_size); stanExports_single_season.h:1592:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_distsamp(const std::vector&, const int&, const T2__&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const int&, const T10__&, std::ostream*) [with T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; T10__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1592 | stan::model::rvalue(conv_const, "conv_const", 1593 | stan::model::index_min_max( 1594 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1595 | stan::model::index_uni(1)), 1596 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1597 | stan::model::index_uni(2)))), pstream__), stanExports_single_season.h:3587:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3587 | get_loglik_distsamp(y, M, aux2, si, lp_state, lp_det, z_dist, 3588 | log_scale, 3589 | stan::model::rvalue(aux1, "aux1", stan::model::index_uni(1)), 3590 | y_dist, aux3, pstream__), "assigning variable log_lik"); stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 35 | check_finite("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 36 | check_finite("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 39 | check_not_nan("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 40 | check_not_nan("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/math/special_functions/beta.hpp:1721, from /usr/local/lib/R/library/BH/include/boost/math/special_functions/binomial.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun.hpp:46, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:14: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp: In instantiation of ‘boost::math::detail::temme_root_finder::temme_root_finder(T, T) [with T = double]’: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: required from ‘T boost::math::detail::temme_method_2_ibeta_inverse(T, T, T, T, T, const Policy&) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 304 | temme_root_finder(-lu, alpha), x, lower, upper, policies::digits() / 2); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:48: required from ‘T boost::math::detail::ibeta_inv_imp(T, T, T, T, const Policy&, T*) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 615 | x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:30: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(T1, T2, T3, T4*, const Policy&) [with T1 = double; T2 = double; T3 = double; T4 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 992 | rx = detail::ibeta_inv_imp( | ~~~~~~~~~~~~~~~~~~~~~^ 993 | static_cast(a), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 994 | static_cast(b), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 995 | static_cast(p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 996 | static_cast(1 - p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 997 | forwarding_policy(), &ry); | ~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:20: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(RT1, RT2, RT3, const Policy&) [with RT1 = double; RT2 = double; RT3 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 1023 | return ibeta_inv(a, b, p, static_cast(nullptr), pol); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:32: required from here 32 | return boost::math::ibeta_inv(a, b, p, boost_policy_t<>()); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable ‘x_extrema’ [-Wunused-variable] 29 | const T x_extrema = 1 / (1 + a); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 1>; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 2, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 2, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 2, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 2, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 2, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 2, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 203 | PanelType panel(m_arg, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:277: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 2, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 2, -1, true> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 100 | pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2256:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2256 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2258:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2258 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2259 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2298 | PacketBlock kernel_half; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2304 | PacketBlock kernel_quarter; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gebp_kernel::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, ResScalar, Index, Index, Index, Index) [with LhsScalar = double; RhsScalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 113 | gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | (std::min)(size,i2), alpha, -1, -1, 0, 0); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1920:103: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1920 | const int SResPacketHalfSize = unpacket_traits::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1921 | const int SResPacketQuarterSize = unpacket_traits::half>::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1977:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1977 | typedef typename conditional=8,typename unpacket_traits::half,SResPacket>::type SResPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1978:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1978 | typedef typename conditional=8,typename unpacket_traits::half,SLhsPacket>::type SLhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1979:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1979 | typedef typename conditional=8,typename unpacket_traits::half,SRhsPacket>::type SRhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1980:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1980 | typedef typename conditional=8,typename unpacket_traits::half,SAccPacket>::type SAccPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from ‘void Eigen::internal::tribb_kernel::operator()(ResScalar*, Index, Index, const LhsScalar*, const RhsScalar*, Index, Index, const ResScalar&) [with LhsScalar = double; RhsScalar = double; Index = long int; int mr = 4; int nr = 4; bool ConjLhs = false; bool ConjRhs = false; int ResInnerStride = 1; int UpLo = 2; ResScalar = double]’ 155 | Matrix buffer((internal::constructor_without_unaligned_array_assert())); | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:26: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:43: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:352:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 352 | Block A21(mat,k+1,k,rs,1); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:80: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:67: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, true>, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_linesearch.hpp:247:0: required from ‘int stan::optimization::WolfeLineSearch(FunctorType&, Scalar&, XType&, Scalar&, XType&, const XType&, const XType&, const Scalar&, const XType&, const Scalar&, const Scalar&, const Scalar&, const Scalar&, const Scalar&) [with FunctorType = ModelAdaptor; Scalar = double; XType = Eigen::Matrix]’ 247 | x1.noalias() = x0 + alpha1 * p; /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 209 | = WolfeLineSearch(_func, _alpha, _xk_1, _fk_1, _gk_1, _pk, _xk, _fk, 210 | _gk, _ls_opts.c1, _ls_opts.c2, _ls_opts.minAlpha, 211 | _ls_opts.maxLSIts, _ls_opts.maxLSRestarts); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from ‘void stan::optimization::BFGSUpdate_HInv::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 55 | pk.noalias() = -(_Hk * gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 254 | _qn.search_direction(_pk, _gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2205:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2205:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_single_season.h:784:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 784 | const auto& logit_p = stan::math::to_ref(logit_p_arg__); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::VectorBlock, -1>]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:892:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3568:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3568 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3569 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3570 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:22: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~~~~~^~ stanExports_single_season.h:892:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3568:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3568 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3569 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3570 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:13: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~^~~~~~~~~~~~ stanExports_single_season.h:892:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3568:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3568 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3569 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3570 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:32: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_single_season.h:892:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3568:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3568 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3569 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3570 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_single_season.h: In instantiation of ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’: stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) stanExports_single_season.h:1024: warning: comparison of integer expressions of different signedness: ‘int’ and ‘size_t’ {aka ‘long unsigned int’} [-Wsign-compare] 1024 | for (int j = 1; j <= stan::math::size(y); ++j) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_single_season.h:1497:0: required from ‘stan::promote_args_t::type, T2__, T3__, T4__, typename stan::base_type::type> model_single_season_namespace::lp_distsamp(const std::vector&, const T1__&, const T2__&, const T3__&, const T4__&, const int&, const int&, const T7__&, std::ostream*) [with T1__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2__ = double; T3__ = double; T4__ = double; T7__ = Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_stan_scalar, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T2__, T3__, T4__, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1497 | const auto& conv_const = stan::math::to_ref(conv_const_arg__); stanExports_single_season.h:1581:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_distsamp(const std::vector&, const int&, const T2__&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const int&, const T10__&, std::ostream*) [with T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; T10__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1581 | lp_distsamp( 1582 | stan::model::rvalue(y, "y", 1583 | stan::model::index_min_max( 1584 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1585 | stan::model::index_uni(1)), 1586 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1587 | stan::model::index_uni(2)))), db, 1588 | stan::model::rvalue(log_lambda, "log_lambda", 1589 | stan::model::index_uni(i)), 1590 | stan::model::rvalue(trans_par1, "trans_par1", 1591 | stan::model::index_uni(i)), trans_par2, point, keyfun, 1592 | stan::model::rvalue(conv_const, "conv_const", 1593 | stan::model::index_min_max( 1594 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1595 | stan::model::index_uni(1)), 1596 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1597 | stan::model::index_uni(2)))), pstream__), stanExports_single_season.h:3587:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3587 | get_loglik_distsamp(y, M, aux2, si, lp_state, lp_det, z_dist, 3588 | log_scale, 3589 | stan::model::rvalue(aux1, "aux1", stan::model::index_uni(1)), 3590 | y_dist, aux3, pstream__), "assigning variable log_lik"); stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from ‘Eigen::MapBase::ScalarWithConstIfNotLvalue& Eigen::MapBase::coeffRef(Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long int]’ 15 | EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 367 | matA.col(i).coeffRef(i+1) = 1; | ~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from ‘void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase&, Eigen::DenseBase&, const Eigen::JacobiRotation&) [with VectorX = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]’ 475 | EIGEN_PLAIN_ENUM_MIN(evaluator::Alignment, evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from ‘void Eigen::MatrixBase::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation&) [with OtherScalar = double; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’ 315 | internal::apply_rotation_in_the_plane(x, y, j.transpose()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:895:24: required from ‘void Eigen::internal::tridiagonal_qr_step(RealScalar*, RealScalar*, Index, Index, Scalar*, Index) [with int StorageOrder = 0; RealScalar = double; Scalar = double; Index = long int]’ 895 | q.applyOnTheRight(k,k+1,rot); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:548:87: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 548 | internal::tridiagonal_qr_step(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, -1, 1, false> >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::min_coeff_visitor, -1, 1, false>, 0>; Derived = Eigen::Block, -1, 1, false>]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:323:14: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 323 | this->visit(minVisitor); | ~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:496:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 496 | return minCoeff(index); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:35: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, true>, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:74: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:50: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from ‘auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_single_season.h:892:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of ‘template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >]’ 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:179:0: required from ‘auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 179 | using op_ret_type = plain_type_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 892 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:183:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_single_season.h: In instantiation of ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’: stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) stanExports_single_season.h:1024: warning: comparison of integer expressions of different signedness: ‘int’ and ‘size_t’ {aka ‘long unsigned int’} [-Wsign-compare] 1024 | for (int j = 1; j <= stan::math::size(y); ++j) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_single_season.h:2106:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2106 | const auto& pars1 = stan::math::to_ref(pars1_arg__); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | = to_ref_if::value>(y_scaled * y_scaled); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from ‘stan::math::var stan::math::accumulator::type>::value, void>::type>::sum() const [with T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value; stan::math::var = stan::math::var_value]’ 135 | inline var sum() const { return stan::math::sum(buf_); } stanExports_single_season.h:3400:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3400 | return lp_accum__.sum(); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, -1>&>(const Eigen::VectorBlock, -1>&):: [with auto:14 = const Eigen::VectorBlock, -1>]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from ‘stan::math::value_of_rec, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:2 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&):: [with auto:14 = const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::; Args = {const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:10: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 63 | (2 * as_array_or_scalar(n_double) - 1)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:41: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 63 | (2 * as_array_or_scalar(n_double) - 1)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:66:49: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 66 | ntheta = forward_as(signs * theta_val); | ~~~~~~^~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:72:38: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 72 | T_partials_array exp_m_ntheta = exp(-ntheta); | ~~~^~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:53: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ^~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:44: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:76:18: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 76 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:41: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~^~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:72: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~^~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper, -1, 1, false> >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:72:62: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 72 | = to_ref_if::value>(inv_logit(-alpha_val)); | ^~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >(const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >&):: [with auto:170 = Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_binary.hpp:231:33: required from ‘stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&):: [with auto:73 = stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; auto:74 = const int; auto:75 = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 231 | return y_inner.unaryExpr( | ~~~~~~~~~~~~~~~~~^ 232 | [f_inner, x_inner](const auto& v) { return f_inner(x_inner, v); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from ‘class stan::math::Holder, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >’ 115 | class Holder | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from ‘auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence, const std::tuple&) [with T = Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; long unsigned int ...Is = {0}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::}; std::index_sequence = std::integer_sequence]’ 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from ‘auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::; long unsigned int ...Is = {0, 1, 2}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&}; std::index_sequence = std::integer_sequence]’ 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:92:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:94:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ^~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 453 | RealScalar scale = mat.cwiseAbs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:34:74: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:60: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3315:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3315 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3316 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3317 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3315:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3315 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3316 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3317 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3315:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3315 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3316 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3317 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: required from ‘stan::math::var stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix, -1, 1>; stan::require_eigen_st* = 0; stan::require_not_var_matrix_t* = 0; var = var_value]’ 76 | += res.adj() * (arena_v_val.array().val() - res.val()).exp().matrix(); stanExports_single_season.h:922:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 922 | return stan::math::log_sum_exp(lp); stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::Array >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log >(const Eigen::Array&):: [with auto:170 = Eigen::Array]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_column_vector_or_scalar.hpp:60:54: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar > >(Eigen::Transpose >&&):: [with auto:14 = Eigen::Transpose >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv > > >(const Eigen::ArrayWrapper > >&):: [with auto:221 = Eigen::ArrayWrapper > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > > >(const Eigen::ArrayWrapper > >&):: [with auto:170 = Eigen::ArrayWrapper > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:98:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square > > >(const Eigen::ArrayWrapper > >&):: [with auto:239 = Eigen::ArrayWrapper > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp >(const Eigen::Array&):: [with auto:216 = Eigen::Array]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:17: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:27: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs >(const Eigen::Array&):: [with auto:10 = Eigen::Array]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&):: [with auto:12 = Eigen::ArrayWrapper, 1, -1> > >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv >(const Eigen::Array&):: [with auto:221 = Eigen::Array]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square >(const Eigen::Array&):: [with auto:239 = Eigen::Array]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, true>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, true>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, true>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 1, -1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 1, -1, true>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:54: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Block, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (2 / (1 + exp_y_minus_mu_div_sigma) - 1) * inv_sigma); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ^~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | const auto& exp_mu_div_sigma = to_ref(exp(mu_val * inv_sigma)); | ~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, -1, 1, false> > >(const Eigen::ArrayWrapper, -1, 1, false> >&):: [with auto:170 = Eigen::ArrayWrapper, -1, 1, false> >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_single_season.h:2122:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_single_season.h:2133:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_single_season.h:2138:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > >(const Eigen::ArrayWrapper >&):: [with auto:170 = Eigen::ArrayWrapper >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:54:16: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 54 | check_not_nan(function, "Logit transformed probability parameter", theta_val); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:795:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 795 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_single_season.h:840:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 840 | lp_occu( 841 | stan::model::rvalue(y, "y", 842 | stan::model::index_min_max( 843 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 844 | stan::model::index_uni(1)), 845 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 846 | stan::model::index_uni(2)))), 847 | stan::model::rvalue(logit_psi, "logit_psi", 848 | stan::model::index_uni(i)), 849 | stan::model::rvalue(logit_p, "logit_p", 850 | stan::model::index_min_max( 851 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 852 | stan::model::index_uni(1)), 853 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 854 | stan::model::index_uni(2)))), 855 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 856 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3559:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3559 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3560 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3561 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:61:15: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 61 | check_finite(function, "Probability parameter", alpha_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3577:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3577 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3578 | log_scale, K, 3579 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3580 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from ‘Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 1, -1, false>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; Eigen::MatrixXd = Eigen::Matrix]’ 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_single_season.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 16, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 16, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 16, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from ‘void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Func = generic_product_impl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]’ 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:333: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 306 | typedef typename Traits::LhsPacket LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:61:15: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 61 | check_finite(function, "Probability parameter", alpha_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:1034:0: required from ‘stan::promote_args_t::type> model_single_season_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1034 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_single_season.h:1074:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_single_season_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1074 | lp_pcount_pois( 1075 | stan::model::rvalue(y, "y", 1076 | stan::model::index_min_max( 1077 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1078 | stan::model::index_uni(1)), 1079 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1080 | stan::model::index_uni(2)))), 1081 | stan::model::rvalue(log_lambda, "log_lambda", 1082 | stan::model::index_uni(i)), 1083 | stan::model::rvalue(logit_p, "logit_p", 1084 | stan::model::index_min_max( 1085 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1086 | stan::model::index_uni(1)), 1087 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1088 | stan::model::index_uni(2)))), K, 1089 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1090 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3333:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3333 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3334 | log_scale, K, 3335 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3336 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 63 | check_finite(function, "Location parameter", mu_val); stanExports_single_season.h:2122:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2122 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_single_season.h:2122:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2122 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:83:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 83 | check_positive_finite(function, "Degrees of freedom parameter", nu_val); stanExports_single_season.h:2133:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2133 | stan::math::student_t_lpdf(x, pars1, pars2, pars3)); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2143:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2143 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, 1, -1>; T_scale = Eigen::Matrix, 1, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_single_season.h:2122:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Matrix, 1, -1>; T3__ = Eigen::Matrix, 1, -1>; T4__ = Eigen::Matrix, 1, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 2122 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Block, -1, 1, false>]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2143:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2143 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_single_season.h:2122:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2122 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:45:15: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 45 | check_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2138:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2138 | out = (out + stan::math::logistic_lpdf(x, pars1, pars2)); stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2143:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2143 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:166:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from ‘static void Eigen::internal::generic_product_impl::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix; LhsT = Eigen::Matrix; RhsT = Eigen::Transpose >; Func = Eigen::internal::assign_op; Scalar = double; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); | ~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp > >(const arena_matrix >&)::; T = stan::math::arena_matrix >]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Array; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Array; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::Array; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 2, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:40: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; Dest = Eigen::Block, -1, 1, false>; typename Dest::Scalar = double]’ 296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; Rhs = Eigen::Transpose >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:88:38: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:959:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_single_season_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 959 | lp_rn( 960 | stan::model::rvalue(y, "y", 961 | stan::model::index_min_max( 962 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 963 | stan::model::index_uni(1)), 964 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 965 | stan::model::index_uni(2)))), 966 | stan::model::rvalue(log_lambda, "log_lambda", 967 | stan::model::index_uni(i)), 968 | stan::model::rvalue(logit_p, "logit_p", 969 | stan::model::index_min_max( 970 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 971 | stan::model::index_uni(1)), 972 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 973 | stan::model::index_uni(2)))), 974 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 975 | stan::model::index_uni(1)), K, 976 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 977 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_single_season.h:3324:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3324 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3325 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3326 | stan::model::index_uni(1)), pstream__), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2202:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_single_season_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2202 | lp_single_prior( 2203 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2204 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2205 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2206 | stan::model::index_min_max(1, 1)), 2207 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2208 | stan::model::index_min_max(1, 1)), 2209 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2210 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2310:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2310 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/broadcast_array.hpp:32:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:2315:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_single_season_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2315 | stan::math::normal_lpdf( 2316 | stan::model::rvalue(b, "b", 2317 | stan::model::index_min_max(idx, 2318 | ((stan::model::rvalue(n_random, "n_random", 2319 | stan::model::index_uni(i)) + idx) - 1))), 0, 2320 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:292:8: required from ‘struct Eigen::internal::evaluator > >’ 292 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_single_season.h:3520:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3520 | stan::math::csr_matrix_times_vector( 3521 | stan::model::rvalue(Zdim_state, "Zdim_state", 3522 | stan::model::index_uni(1)), 3523 | stan::model::rvalue(Zdim_state, "Zdim_state", 3524 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3525 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:31: /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: required from ‘bool boost::range::equal(const SinglePassRange1&, const SinglePassRange2&) [with SinglePassRange1 = boost::iterator_range<__gnu_cxx::__normal_iterator > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/iterator_range_core.hpp:644:32: required from ‘bool boost::operator==(const iterator_range&, const iterator_range&) [with Iterator1T = __gnu_cxx::__normal_iterator >; Iterator2T = __gnu_cxx::__normal_iterator >]’ 644 | return boost::equal( l, r ); | ~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from ‘bool boost::algorithm::split_iterator::equal(const boost::algorithm::split_iterator&) const [with IteratorT = __gnu_cxx::__normal_iterator >]’ 359 | m_Match==Other.m_Match && /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:649:26: required from ‘static bool boost::iterators::iterator_core_access::equal(const Facade1&, const Facade2&, mpl_::true_) [with Facade1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; mpl_::true_ = mpl_::bool_]’ 649 | return f1.equal(f2); | ~~~~~~~~^~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator==(const iterator_facade&, const iterator_facade&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference1 = long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:337: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 62 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 63 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3370:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3370 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3371 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_single_season.h:2143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_single_season.h:2149:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_single_season.h:3382:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3382 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3383 | b_state, n_random_state, sigma_state, 3384 | stan::model::rvalue(prior_dist_state, 3385 | "prior_dist_state", stan::model::index_uni(3)), 3386 | prior_pars_state, pstream__)); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, false>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:81:75: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 81 | gemm_pack_rhs pack_rhs; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::CopyConstructible::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 167 | BOOST_CONCEPT_USAGE(CopyConstructible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::IncrementableIteratorConcept::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 136 | BOOST_CONCEPT_USAGE(IncrementableIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::EqualityComparable::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 233 | BOOST_CONCEPT_USAGE(EqualityComparable) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:166: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h: In instantiation of ‘Index Eigen::internal::first_default_aligned(const Scalar*, Index) [with Scalar = double; Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’ 89 | Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 500 | return first_aligned::alignment>(array, size); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:169:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheRight(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 169 | this->col(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:304:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 131 | this->row(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 132 | bottom.noalias() -= tau * essential * tmp; | ~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:184:17: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 184 | pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 1; bool ConjugateLhs = false; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 346 | pack_rhs_panel(blockB+j2*actual_kc, | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ 347 | rhs.getSubMapper(actual_k2+panelOffset, actual_j2), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 348 | panelLength, actualPanelWidth, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | actual_kc, panelOffset); | ~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]’ 783 | triangular_product_impl::run(dst, lhs, rhs.nestedExpression(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 2>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 2>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 2>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, 1>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, 1>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, 1>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 5>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, true>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 233 | gemm_pack_rhs pack_rhs_panel; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:42: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:57: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:73:50: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Transpose, -1, -1, false>, 1, -1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; ExpressionType = Eigen::Block, -1, -1, false>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 319 | pack_lhs_panel(blockA, lhs.getSubMapper(i2,absolute_j2), | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 320 | actualPanelWidth, actual_mc, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 321 | actual_kc, j2); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 150 | Matrix triangularBuffer(a); | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 153 | triangularBuffer.diagonal().setZero(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from ‘ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]’ 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:444:18: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:282:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >’ 282 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Derived = Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_single_season.h:3276:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3276 | stan::math::csr_matrix_times_vector( 3277 | stan::model::rvalue(Zdim_state, "Zdim_state", 3278 | stan::model::index_uni(1)), 3279 | stan::model::rvalue(Zdim_state, "Zdim_state", 3280 | stan::model::index_uni(2)), Zw_state, Zv_state, Zu_state, 3281 | b_state)), "assigning variable lp_state"); stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from ‘void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, Eigen::Transpose >, 1> >; Functor = Eigen::internal::assign_op; int Version = 1; Eigen::Index = long int]’ 654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col)); | ~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Derived = Eigen::Block, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from ‘Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, false>; Scalar = double]’ 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::OuterStride<> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:39:18: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:57: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:42: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:301:29: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block, -1, -1, false>; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; int Side = 1; int Mode = 2]’ 71 | triangular_solve_vector | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:32: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]’ 194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, 1, false>]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_single_season_namespace::model_single_season; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_single_season.h:3265:0: required from ‘stan::scalar_type_t model_single_season_namespace::model_single_season::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3265 | stan::math::add(stan::math::multiply(X_state, beta_state), stanExports_single_season.h:4106:0: required from ‘T_ model_single_season_namespace::model_single_season::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4106 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_single_season_namespace::model_single_season; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_single_season.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/access_helpers.hpp:92:0: required from ‘void stan::model::internal::assign_impl(T1&&, T2&&, const char*) [with T1 = Eigen::Matrix&; T2 = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_all_eigen_t* = 0]’ 92 | x = std::forward(y); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from ‘void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]’ 60 | internal::assign_impl(x, std::forward(y), name); stanExports_single_season.h:3508:0: required from ‘void model_single_season_namespace::model_single_season::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3508 | stan::model::assign(lp_state, 3509 | stan::math::add(stan::math::multiply(X_state, beta_state), 3510 | offset_state), "assigning variable lp_state"); stanExports_single_season.h:4095:0: required from ‘void model_single_season_namespace::model_single_season::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4095 | write_array_impl(base_rng, params_r, params_i, vars, 4096 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_single_season.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 341 | dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false> >, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false> >, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::InnerStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::InnerStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::InnerStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:106: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block, -1, -1, false>, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 327 | internal::triangular_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 328 | | ~~~~~~~~~ 332 | ::run(actualLhs.rows(),actualLhs.cols(), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 333 | actualLhs.data(),actualLhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 334 | actualRhsPtr,1, | ~~~~~~~~~~~~~~~ 335 | dest.data(),dest.innerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 336 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:27: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_single_season_namespace::model_single_season; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_single_season_namespace::model_single_season; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_single_season.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::sum > >(const std::vector, arena_allocator > >&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl, 0, Eigen::Stride<0, 0> >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_single_season_namespace::model_single_season; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppArmadillo/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c stanExports_spatial.cc -o stanExports_spatial.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:3, from stanExports_spatial.h:23, from stanExports_spatial.cc:5: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:18, from /usr/local/lib/R/library/BH/include/boost/shared_ptr.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/time_clock.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:15, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:4: /usr/local/lib/R/library/BH/include/boost/smart_ptr/detail/shared_count.hpp:361:33: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 361 | explicit shared_count( std::auto_ptr & r ): pi_( new sp_counted_impl_p( r.get() ) ) | ^~~~~~~~ In file included from /usr/include/c++/14/memory:78, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:7: /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:251:65: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 251 | template< class T, class R > struct sp_enable_if_auto_ptr< std::auto_ptr< T >, R > | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:508:31: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 508 | explicit shared_ptr( std::auto_ptr & r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:521:22: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 521 | shared_ptr( std::auto_ptr && r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:604:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 604 | shared_ptr & operator=( std::auto_ptr & r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:613:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 613 | shared_ptr & operator=( std::auto_ptr && r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function ‘boost::shared_ptr& boost::shared_ptr::operator=(std::auto_ptr<_Up>&&)’: /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:615:38: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 615 | this_type( static_cast< std::auto_ptr && >( r ) ).swap( *this ); | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from ‘struct Eigen::internal::traits > >’ 19 | template struct traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from ‘class Eigen::SolverBase > >’ 68 | class SolverBase : public EigenBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from ‘class Eigen::LDLT >’ 59 | template class LDLT | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from ‘class Eigen::LDLT >’ 69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from ‘class Eigen::LDLT >’ 287 | TmpMatrixType m_temporary; | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:29: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:41: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:45: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:26: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:34: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_array.hpp:37:49: required from here 37 | Eigen::VectorXd v = Eigen::VectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:28: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:39: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:53: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:72: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:77: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:17: required from here 71 | A.diagonal().array() -= mu; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:29: required from here 71 | A.diagonal().array() -= mu; | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:22: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:38: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:178:58: required from here 178 | alpha = Eigen::VectorXd::Constant(_p_max - 1, normA); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::internal::member_minCoeff, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::internal::member_minCoeff, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::internal::member_minCoeff, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, Eigen::internal::member_minCoeff, 0>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:203:38: required from here 203 | int cost = c.colwise().minCoeff().minCoeff(&m); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/one_hot_row_vector.hpp:25:52: required from here 25 | Eigen::RowVectorXd ret = Eigen::RowVectorXd::Zero(K); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:13:64: required from here 13 | : m_(Eigen::VectorXd::Zero(n)), m2_(Eigen::MatrixXd::Zero(n, n)) { | ~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:26:31: required from here 26 | Eigen::VectorXd delta(q - m_); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:38: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:37:40: required from here 37 | covar = m2_ / (num_samples_ - 1.0); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_var_estimator.hpp:28:30: required from here 28 | m2_ += delta.cwiseProduct(q - m_); | ~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here 77 | Eigen::Map(dz_dt.data(), dz_dt.size()) = f_y_t; | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:13, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:43: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combination(std::vector&, const int&, const int&, const int&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:73:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 73 | for (std::size_t i = 0; i < p - 1; i++) { | ~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:79:16: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 79 | } while (k < x); | ~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:102:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 102 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:105:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 105 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::increment(std::vector&, const int&, const double&, const std::vector&, std::vector&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:126:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 126 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 132 | while ((first_zero < index.size()) && index[first_zero]) { | ~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 135 | if (first_zero == index.size()) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:143:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 143 | for (std::size_t i = 0; i != first_zero + 1; i++) { | ~~^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:168:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 168 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here 40 | coupled_state.size()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/mpl/aux_/na_assert.hpp:23, from /usr/local/lib/R/library/BH/include/boost/mpl/arg.hpp:25, from /usr/local/lib/R/library/BH/include/boost/mpl/placeholders.hpp:24, from /usr/local/lib/R/library/BH/include/boost/mpl/apply.hpp:24, from /usr/local/lib/R/library/BH/include/boost/serialization/array_optimization.hpp:18, from /usr/local/lib/R/library/BH/include/boost/serialization/array_wrapper.hpp:21, from /usr/local/lib/R/library/BH/include/boost/serialization/array.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:22, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/vector.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint.hpp:25, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:16: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp: At global scope: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: warning: unnecessary parentheses in declaration of ‘assert_arg’ [-Wparentheses] 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ | - 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ | - /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of ‘assert_not_arg’ [-Wparentheses] 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | - 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ | - In file included from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/traits.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:27: /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:111:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 111 | public std::iterator { | ^~~~~~~~ In file included from /usr/include/c++/14/bits/stl_algobase.h:65, from /usr/include/c++/14/bits/specfun.h:43, from /usr/include/c++/14/cmath:3898, from /usr/local/lib/R/library/Rcpp/include/Rcpp/platform/compiler.h:100, from /usr/local/lib/R/library/Rcpp/include/Rcpp/r/headers.h:66, from /usr/local/lib/R/library/Rcpp/include/RcppCommon.h:30, from /usr/local/lib/R/library/Rcpp/include/Rcpp.h:27, from stanExports_spatial.cc:3: /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:149:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 149 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:204:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 204 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/invoke.hpp:52, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/adapter/fused.hpp:17, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/generation/make_fused.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/include/make_fused.hpp:11, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:28, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33: /usr/local/lib/R/library/BH/include/boost/get_pointer.hpp:48:40: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 48 | template T * get_pointer(std::auto_ptr const& p) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:38:59: required from here 38 | Eigen::VectorXd stddev = S_ldlt.vectorD().array().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 5>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:75: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:76: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:135:41: required from here 135 | Eigen::VectorXd(F.transpose() * theta_t), V_ldlt, rng); | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_hidden_state_prob.hpp:77:52: required from here 77 | alphas.col(n) = alphas.col(n).cwiseProduct(beta); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_latent_rng.hpp:71:73: required from here 71 | probs_vec = alphas.col(n_transitions) / alphas.col(n_transitions).sum(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::TriangularView >, 2>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::TriangularView >, 2>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::TriangularView >, 2>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:42: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::TriangularView >, 2>, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:25:32: required from here 25 | S_inv = ldlt_of_S.solve(S_inv); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:47: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:54: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:109:64: required from here 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Matrix >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: recursively required by substitution of ‘template const Eigen::internal::triangular_solve_retval >, 6>, Other> Eigen::TriangularViewImpl >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase&) const [with int Side = ; Other = ]’ 108 | * (D_ldlt.matrixU().solve( | ~~~~~~~~~~~~~~~~~~~~~~^ 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from ‘struct Eigen::internal::accessors_level >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 32 | enum { has_direct_access = (traits::Flags & DirectAccessBit) ? 1 : 0, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:43: required from here 110 | .transpose() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:51: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:52: required from here 111 | * D_ldlt.transpositionsP()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/multinomial_logit_lpmf.hpp:39:0: required from here 39 | lp += lgamma(1 + ns_map.sum()) - lgamma(1 + ns_map).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_ccdf_log.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob.hpp:240, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:16: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp: In function ‘stan::return_type_t stan::math::normal_lccdf(const T_y&, const T_loc&, const T_scale&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: ‘-Wmisleading-indentation’ is disabled from this point onwards, since column-tracking was disabled due to the size of the code/headers 68 | } else if (scaled_diff > 8.25 * INV_SQRT_TWO) { /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lccdf.hpp:68: note: adding ‘-flarge-source-files’ will allow for more column-tracking support, at the expense of compilation time and memory /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp: In member function ‘virtual std::vector > stan::io::dump::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 694 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 707 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here 102 | if (C_adj.size() > 0) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here 111 | = D_adj.adjoint().template triangularView(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1, -1, false>, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here 116 | D_adj.diagonal() *= 0.5; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from ‘class Eigen::RefBase, 0, Eigen::OuterStride<> > >’ 59 | template class RefBase | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from ‘class Eigen::Ref, 0, Eigen::OuterStride<> >’ 281 | template class Ref | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from ‘class Eigen::LLT, 0, Eigen::OuterStride<> >, 1>’ 76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:142:0: required from here 142 | check_pos_definite("cholesky_decompose", "m", L_factor); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here 144 | L_A.template triangularView().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_factor_constrain.hpp:42:0: required from here 42 | y_val.row(m).head(m) = x.val().segment(pos, m); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of ‘template static std::true_type stan::is_base_pointer_convertible >::f(const Eigen::EigenBase*) [with OtherDerived = ]’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible >’ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from ‘struct stan::is_eigen >’ 21 | : bool_constant::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of ‘template class stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix]’ 301 | (is_eigen::value || is_kernel_expression_and_not_scalar::value) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 1>’ 148 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 222 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from ‘class stan::math::arena_matrix, void>’ 129 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from ‘class stan::math::vari_value, void>’ 814 | using InnerIterator = typename arena_matrix::InnerIterator; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from ‘const auto& stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 419 | inline const auto& val() const noexcept { return vi_->val(); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from ‘class Eigen::Tridiagonalization >’ 97 | >::type SubDiagonalReturnType; | ^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from ‘class Eigen::SelfAdjointEigenSolver >’ 111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here 40 | arena_t eigenvals = solver.eigenvalues(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here 27 | g = x.adj(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0> > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:51:0: required from here 51 | reverse_pass_callback([arena_M, log_det, arena_M_inv_transpose]() mutable { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:73:0: required from here 73 | vector_d diff = (x_d.array() - x_d.maxCoeff()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here 81 | Eigen::Map(softmax_x_d_array, a_size) = softmax_x_d.array() / sum; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:50:0: required from here 50 | arena_powers[0] = Eigen::MatrixXd::Identity(N, N); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:53:0: required from here 53 | arena_powers[i] = arena_powers[1] * arena_powers[i - 1]; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:63:0: required from here 63 | adj_M += adj_C * arena_powers[i - 1].transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here 67 | Eigen::Map(variRefB_, M_, N_).adj() += adjB; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from here 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:55:0: required from here 55 | L.col(0).tail(pull) = CPCs.val().head(pull); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:56:0: required from here 56 | arena_acc.tail(pull) = 1.0 - CPCs.val().head(pull).array().square(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:63:0: required from here 63 | L.col(i).tail(pull) = cpc_seg * arena_acc.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_cov_matrix.hpp:56:0: required from here 56 | sds.adj() += (prod.adj().cwiseProduct(corr_L.val())).rowwise().sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/rows_dot_self.hpp:41:0: required from here 41 | x.adj() += (2 * res.adj()).asDiagonal() * x.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0, Eigen::Stride<0, 0> >, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here 56 | arena_Fp.diagonal().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here 70 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from ‘struct Eigen::internal::traits, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 278 | typedef typename DiagonalVectorType::Scalar Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from ‘class Eigen::DiagonalBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 18 | class DiagonalBase : public EigenBase | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from ‘class Eigen::DiagonalWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 293 | class DiagonalWrapper | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:63:0: required from here 63 | + arena_U * arena_D.asDiagonal().inverse() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here 80 | v1_map.adj() += di; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:23:0: required from here 23 | vector_d dtrs_vals = dtrs_map.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::val_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here 26 | fx = fx_var.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&):: [with auto:12 = const Eigen::Matrix, -1, 1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::; Args = {const Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from ‘auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]’ 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/algebra_solver_fp.hpp:101:0: required from here 101 | y_dummy(stan::math::value_of(y)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here 604 | f_y_t_vars.adj() = -Eigen::Map(NV_DATA_S(yB), N_); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/finite_diff_hessian_times_vector_auto.hpp:62:0: required from here 62 | hvp = (grad_forward - grad_backward) / (2 * epsilon); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/initialize.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:49: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function ‘virtual std::vector > stan::io::random_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 111 | for (comp_iter = 0, real_iter = 0; real_iter < val_r.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:182:0: required from here 182 | return normal_fullrank(Eigen::VectorXd(mu_.array().square()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:183:0: required from here 183 | Eigen::MatrixXd(L_chol_.array().square())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:197:0: required from here 197 | return normal_fullrank(Eigen::VectorXd(mu_.array().sqrt()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:198:0: required from here 198 | Eigen::MatrixXd(L_chol_.array().sqrt())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:263:0: required from here 263 | L_chol_.array() /= rhs.L_chol().array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:459:0: required from here 459 | L_grad.diagonal().array() += L_chol_.diagonal().array().inverse(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:370:0: required from here 370 | omega_grad.array() += tmp_mu_grad.array().cwiseProduct(eta.array()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:388:0: required from here 388 | omega_grad.array() = omega_grad.array().cwiseProduct(omega_.array().exp()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/nuts/base_nuts.hpp:175:0: required from here 175 | rho = rho_bck + rho_fwd; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 2>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 2>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 2>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 2>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 2>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:53:0: required from here 53 | z.p = z.inv_e_metric_.llt().matrixU().solve(u); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from ‘auto stan::math::to_matrix(const std::vector&, int, int) [with T = double]’ 133 | return Eigen::Map>( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 134 | &x[0], m, n); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/read_dense_inv_metric.hpp:33:0: required from here 33 | inv_metric = stan::math::to_matrix(dense_vals, num_params, num_params); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here 27 | covar = (n / (n + 5.0)) * covar /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of ‘template typename Eigen::ScalarBinaryOpTraits::Scalar, Eigen::internal::scalar_product_op::Scalar> >::ReturnType Eigen::MatrixBase >::dot(const Eigen::MatrixBase&) const [with OtherDerived = ]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here 27 | var = (n / (n + 5.0)) * var /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:68: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function ‘virtual std::vector > stan::io::array_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 304 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 317 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue_varmat.hpp:145:0: required from here 145 | x_ret_vals.coeffRef(j) = x.val().coeff(row_idx_val, col_idx_vals[j]); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_header.hpp:11, from stanExports_spatial.h:25: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp: At global scope: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:159: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(std::vector, std::allocator > >&, std::vector&, std::ostream*) const [with M = model_spatial_namespace::model_spatial; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 159 | inline math::var log_prob(std::vector& theta, stanExports_spatial.h:4362: note: by ‘model_spatial_namespace::model_spatial::log_prob’ 4362 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:154: warning: ‘double stan::model::model_base_crtp::log_prob(std::vector&, std::vector&, std::ostream*) const [with M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 154 | inline double log_prob(std::vector& theta, std::vector& theta_i, stanExports_spatial.h:4362: note: by ‘model_spatial_namespace::model_spatial::log_prob’ 4362 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:96: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(Eigen::Matrix, -1, 1>&, std::ostream*) const [with M = model_spatial_namespace::model_spatial; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 96 | inline math::var log_prob(Eigen::Matrix& theta, stanExports_spatial.h:4362: note: by ‘model_spatial_namespace::model_spatial::log_prob’ 4362 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:91: warning: ‘double stan::model::model_base_crtp::log_prob(Eigen::VectorXd&, std::ostream*) const [with M = model_spatial_namespace::model_spatial; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 91 | inline double log_prob(Eigen::VectorXd& theta, stanExports_spatial.h:4362: note: by ‘model_spatial_namespace::model_spatial::log_prob’ 4362 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from ‘struct Eigen::internal::cast_return_type, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 513 | typedef typename _CastType::Scalar NewScalarType; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:48:179: required from ‘struct Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr’ 48 | template struct CastXpr { typedef typename internal::cast_return_type, const Derived> >::type Type; }; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:47:52: required from ‘auto stan::math::append_row(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0]’ 47 | result.topRows(Arows) = A.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_spatial.h:3357:0: required from here 3357 | stan::math::append_row(X_state, X_aug), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:47:17: required from ‘auto stan::math::append_row(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0]’ 47 | result.topRows(Arows) = A.template cast(); | ~~~~~~~~~~~~~~^~~~~~~ stanExports_spatial.h:3361:0: required from here 3361 | stan::math::append_row(offset_state, offset_aug), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from ‘struct Eigen::internal::cast_return_type, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 513 | typedef typename _CastType::Scalar NewScalarType; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:48:179: required from ‘struct Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr’ 48 | template struct CastXpr { typedef typename internal::cast_return_type, const Derived> >::type Type; }; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:47:52: required from ‘auto stan::math::append_row(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0]’ 47 | result.topRows(Arows) = A.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_spatial.h:3361:0: required from here 3361 | stan::math::append_row(offset_state, offset_aug), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:102:18: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0; stan::return_type_t = double]’ 102 | x.unaryExpr([lb, &lp](auto&& xx) { return lb_constrain(xx, lb, lp); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3709:0: required from here 3708 | sigma_state = in__.template read_constrain_lb< 3709 | Eigen::Matrix, jacobian__>(0, 3710 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:83:26: required from ‘auto stan::math::lb_constrain(T&&, L&&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = const int&; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 83 | return eval(x.unaryExpr([lb](auto&& x) { return lb_constrain(x, lb); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:388:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]’ 388 | return stan::math::lb_constrain(this->read(sizes...), lb); stanExports_spatial.h:3709:0: required from here 3708 | sigma_state = in__.template read_constrain_lb< 3709 | Eigen::Matrix, jacobian__>(0, 3710 | lp__, n_group_vars_state); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from ‘auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]’ 107 | return m1 * m2; | ~~~^~~~ stanExports_spatial.h:3761:0: required from here 3761 | stan::math::add(stan::math::multiply(X_state_all, beta_state), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Mat2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_spatial.h:3761:0: required from here 3761 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3762 | offset_state_all), "assigning variable lp_state"); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_spatial.h:3769:0: required from here 3769 | stan::math::add(stan::model::deep_copy(lp_state), 3770 | stan::math::multiply(Kmat, b_state)), "assigning variable lp_state"); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from ‘struct Eigen::internal::traits >’ 17 | struct traits > : traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar&>(const std::vector&)::; Args = {const std::vector >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:72:21: required from ‘auto stan::math::as_array_or_scalar(T&&) [with T = const std::vector&; stan::require_std_vector_t* = 0; stan::require_not_std_vector_t::type>* = 0]’ 72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | std::forward(v)); | ~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:39: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:43: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:55: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&):: [with auto:10 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&)::; T2 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_t::type> >* = 0; T = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from ‘auto stan::math::fabs(const Container&) [with Container = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_container_st* = 0]’ 66 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:37: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&)::; T2 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_t::type> >* = 0; T = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:49:25: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk)); | ~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:22: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long unsigned int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here 97 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { stanExports_spatial.h: In instantiation of ‘void model_spatial_namespace::model_spatial::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = std::vector; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_spatial.h:4390:0: required from here 4390 | unconstrain_array_impl(params_constrained, params_i, 4391 | params_unconstrained, pstream); stanExports_spatial.h:3884: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 3884 | int pos__ = std::numeric_limits::min(); stanExports_spatial.h: In instantiation of ‘void model_spatial_namespace::model_spatial::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = Eigen::Matrix; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_spatial.h:4400:0: required from here 4400 | unconstrain_array_impl(params_constrained, params_i, 4401 | params_unconstrained, pstream); stanExports_spatial.h:3884: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 3884 | int pos__ = std::numeric_limits::min(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp: In instantiation of ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’: stanExports_spatial.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1252: warning: variable ‘ret’ set but not used [-Wunused-but-set-variable] 1252 | int ret = stan::services::error_codes::CONFIG; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 182 | Eigen::Matrix b_args(1); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:117:39: required from ‘TupleT stan::math::internal::grad_2F1_impl_ab(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 117 | inner_diff = g_current.array().abs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:204:78: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 204 | grad_tuple_ab = grad_2F1_impl_ab( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 205 | a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:12: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:47:0: required from here 47 | stan::math::check_not_nan(function, "Mean vector", mu); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:74:0: required from here 74 | stan::math::check_not_nan(function, "Cholesky factor", L_chol); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 207 | for (size_t i = 0; i < x.rows(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 208 | for (size_t j = 0; j < x.cols(); j++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:21:0: required from here 21 | stan::math::check_finite("check_finite", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:22:0: required from here 22 | stan::math::check_positive("check_positive", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here 30 | if (!var.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta.hpp:70, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:10: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp: In instantiation of ‘void stan::math::check_less_or_equal(const char*, const char*, const T_y&, const T_high&, Idxs ...) [with T_y = long unsigned int; T_high = long int; stan::require_all_stan_scalar_t* = 0; Idxs = {}]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’ 79 | stan::math::check_less_or_equal("validate_dims", "array_var_context", 80 | elem_dims_total[dims.size()], array_size); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp:39:20: warning: comparison of integer expressions of different signedness: ‘const long unsigned int’ and ‘const long int’ [-Wsign-compare] 39 | if (unlikely(!(y <= high))) { | ~~~^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/compiler_attributes.hpp:9:41: note: in definition of macro ‘unlikely’ 9 | #define unlikely(x) __builtin_expect(!!(x), 0) | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:21: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_spatial.h:4093:0: required from ‘void model_spatial_namespace::model_spatial::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 4093 | out__.write_free_lb(0, sigma_state); stanExports_spatial.h:4381:0: required from here 4381 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:32: required from ‘auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]’ 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_spatial.h:4093:0: required from ‘void model_spatial_namespace::model_spatial::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 4093 | out__.write_free_lb(0, sigma_state); stanExports_spatial.h:4381:0: required from here 4381 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_spatial.h:4093:0: required from ‘void model_spatial_namespace::model_spatial::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 4093 | out__.write_free_lb(0, sigma_state); stanExports_spatial.h:4381:0: required from here 4381 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:170 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_spatial.h:4093:0: required from ‘void model_spatial_namespace::model_spatial::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 4093 | out__.write_free_lb(0, sigma_state); stanExports_spatial.h:4381:0: required from here 4381 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from ‘auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from ‘void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; L = int; T = double]’ 253 | this->write(stan::math::lb_free(x, lb)); stanExports_spatial.h:4093:0: required from ‘void model_spatial_namespace::model_spatial::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]’ 4093 | out__.write_free_lb(0, sigma_state); stanExports_spatial.h:4381:0: required from here 4381 | transform_inits_impl(context, vars, pstream__); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp: In instantiation of ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; Eigen::MatrixXd = Eigen::Matrix]’: /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_spatial.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: ‘std::vector >::size_type’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 55 | if (p_names.size() != draws.cols()) { /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:71: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 71 | for (size_t i = 0; i < draws.rows(); ++i) { In file included from /usr/local/lib/R/library/BH/include/boost/concept/assert.hpp:35, from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:19, from /usr/local/lib/R/library/BH/include/boost/range/size_type.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/size.hpp:21, from /usr/local/lib/R/library/BH/include/boost/range/functions.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range.hpp:18, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:22: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept >, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:26, from /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:16, from /usr/local/lib/R/library/BH/include/boost/algorithm/string.hpp:23, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:46: /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::token_finderF >; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:98:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FormatterConcept >, boost::algorithm::detail::first_finderF, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:103:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function ‘void boost::algorithm::FormatterConcept::constraints() [with FormatterT = boost::algorithm::detail::const_formatF >; FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 65 | void constraints() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:330: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 72 | typedef blas_data_mapper ResMapper; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 451 | subdiag = mat.template diagonal<-1>().real(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 1, -1, false>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 191 | _pk.noalias() = -_gk; /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:192:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 192 | auto exp_x = to_arena(arena_x.val().array().exp()); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:193:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 193 | arena_t ret = exp_x + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&):: [with auto:12 = const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from ‘auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]’ 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; /usr/local/lib/R/library/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from ‘auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]’ 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_spatial.h:3478:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3477 | sigma_state = in__.template read_constrain_lb< 3478 | Eigen::Matrix, jacobian__>(0, 3479 | lp__, n_group_vars_state); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:34:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 34 | auto arena_A_val = to_arena(arena_A.val()); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 36 | using return_t stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 47 | arena_A.adj() += res_adj * arena_B_val.transpose(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&):: [with auto:12 = stan::math::arena_matrix, -1, -1>, void>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 66 | = return_var_matrix_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:14 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), 3516 | offset_state_all), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 114 | using ret_type = return_var_matrix_t; stanExports_spatial.h:3523:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3523 | stan::math::add(stan::model::deep_copy(lp_state), 3524 | stan::math::multiply(Kmat, b_state)), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]’ 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_spatial.h:3523:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3523 | stan::math::add(stan::model::deep_copy(lp_state), 3524 | stan::math::multiply(Kmat, b_state)), "assigning variable lp_state"); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:255:7: required from ‘class Eigen::Map >’ 255 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:95:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 95 | = decltype((std::declval() * value_of(b)).eval()); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> >&>(arena_matrix, -1, 1> >&):: [with auto:12 = stan::math::arena_matrix, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:128:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 128 | arena_t res = w_val_mat * value_of(b_arena); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:135:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 135 | arena_t res = w_mat_arena.val() * b_arena; stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_spatial.h:3776:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3776 | stan::math::csr_matrix_times_vector( 3777 | stan::model::rvalue(Zdim_det, "Zdim_det", 3778 | stan::model::index_uni(1)), 3779 | stan::model::rvalue(Zdim_det, "Zdim_det", 3780 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from ‘auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Matrix&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]’ 187 | return v.segment(slice_start, slice_size); stanExports_spatial.h:881:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from ‘auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Map, 0, Eigen::Stride<0, 0> >&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]’ 187 | return v.segment(slice_start, slice_size); stanExports_spatial.h:1624:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_distsamp(const std::vector&, const int&, const T2__&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const int&, const T10__&, std::ostream*) [with T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; T10__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1624 | stan::model::rvalue(conv_const, "conv_const", 1625 | stan::model::index_min_max( 1626 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1627 | stan::model::index_uni(1)), 1628 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1629 | stan::model::index_uni(2)))), pstream__), stanExports_spatial.h:3831:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3831 | get_loglik_distsamp(y, M, aux2, si, lp_state, lp_det, z_dist, 3832 | log_scale, 3833 | stan::model::rvalue(aux1, "aux1", stan::model::index_uni(1)), 3834 | y_dist, aux3, pstream__), "assigning variable log_lik"); stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 35 | check_finite("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 36 | check_finite("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 39 | check_not_nan("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 40 | check_not_nan("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/math/special_functions/beta.hpp:1721, from /usr/local/lib/R/library/BH/include/boost/math/special_functions/binomial.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun.hpp:46, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:14: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp: In instantiation of ‘boost::math::detail::temme_root_finder::temme_root_finder(T, T) [with T = double]’: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: required from ‘T boost::math::detail::temme_method_2_ibeta_inverse(T, T, T, T, T, const Policy&) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 304 | temme_root_finder(-lu, alpha), x, lower, upper, policies::digits() / 2); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:48: required from ‘T boost::math::detail::ibeta_inv_imp(T, T, T, T, const Policy&, T*) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 615 | x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:30: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(T1, T2, T3, T4*, const Policy&) [with T1 = double; T2 = double; T3 = double; T4 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 992 | rx = detail::ibeta_inv_imp( | ~~~~~~~~~~~~~~~~~~~~~^ 993 | static_cast(a), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 994 | static_cast(b), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 995 | static_cast(p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 996 | static_cast(1 - p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 997 | forwarding_policy(), &ry); | ~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:20: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(RT1, RT2, RT3, const Policy&) [with RT1 = double; RT2 = double; RT3 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 1023 | return ibeta_inv(a, b, p, static_cast(nullptr), pol); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:32: required from here 32 | return boost::math::ibeta_inv(a, b, p, boost_policy_t<>()); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable ‘x_extrema’ [-Wunused-variable] 29 | const T x_extrema = 1 / (1 + a); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 1>; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 2, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 2, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 2, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 2, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 2, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 2, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 203 | PanelType panel(m_arg, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:277: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 2, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 2, -1, true> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 100 | pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2256:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2256 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2258:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2258 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2259 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2298 | PacketBlock kernel_half; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2304 | PacketBlock kernel_quarter; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gebp_kernel::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, ResScalar, Index, Index, Index, Index) [with LhsScalar = double; RhsScalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 113 | gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | (std::min)(size,i2), alpha, -1, -1, 0, 0); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1920:103: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1920 | const int SResPacketHalfSize = unpacket_traits::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1921 | const int SResPacketQuarterSize = unpacket_traits::half>::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1977:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1977 | typedef typename conditional=8,typename unpacket_traits::half,SResPacket>::type SResPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1978:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1978 | typedef typename conditional=8,typename unpacket_traits::half,SLhsPacket>::type SLhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1979:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1979 | typedef typename conditional=8,typename unpacket_traits::half,SRhsPacket>::type SRhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1980:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1980 | typedef typename conditional=8,typename unpacket_traits::half,SAccPacket>::type SAccPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from ‘void Eigen::internal::tribb_kernel::operator()(ResScalar*, Index, Index, const LhsScalar*, const RhsScalar*, Index, Index, const ResScalar&) [with LhsScalar = double; RhsScalar = double; Index = long int; int mr = 4; int nr = 4; bool ConjLhs = false; bool ConjRhs = false; int ResInnerStride = 1; int UpLo = 2; ResScalar = double]’ 155 | Matrix buffer((internal::constructor_without_unaligned_array_assert())); | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:26: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:43: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:352:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 352 | Block A21(mat,k+1,k,rs,1); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:80: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:67: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, true>, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_linesearch.hpp:247:0: required from ‘int stan::optimization::WolfeLineSearch(FunctorType&, Scalar&, XType&, Scalar&, XType&, const XType&, const XType&, const Scalar&, const XType&, const Scalar&, const Scalar&, const Scalar&, const Scalar&, const Scalar&) [with FunctorType = ModelAdaptor; Scalar = double; XType = Eigen::Matrix]’ 247 | x1.noalias() = x0 + alpha1 * p; /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 209 | = WolfeLineSearch(_func, _alpha, _xk_1, _fk_1, _gk_1, _pk, _xk, _fk, 210 | _gk, _ls_opts.c1, _ls_opts.c2, _ls_opts.minAlpha, 211 | _ls_opts.maxLSIts, _ls_opts.maxLSRestarts); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from ‘void stan::optimization::BFGSUpdate_HInv::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 55 | pk.noalias() = -(_Hk * gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 254 | _qn.search_direction(_pk, _gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2237:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2237:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_spatial.h:816:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 816 | const auto& logit_p = stan::math::to_ref(logit_p_arg__); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::VectorBlock, -1>]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:924:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3812:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3812 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3813 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3814 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:22: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~~~~~^~ stanExports_spatial.h:924:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3812:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3812 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3813 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3814 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:13: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~^~~~~~~~~~~~ stanExports_spatial.h:924:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3812:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3812 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3813 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3814 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:32: required from ‘auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::CwiseUnaryOp, -1>, void>::apply(const Eigen::VectorBlock, -1>&)::, const Eigen::Block, -1, 1, false> >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 62 | return (c - m.array()).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_spatial.h:924:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3812:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3812 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3813 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3814 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_spatial.h: In instantiation of ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’: stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) stanExports_spatial.h:1056: warning: comparison of integer expressions of different signedness: ‘int’ and ‘size_t’ {aka ‘long unsigned int’} [-Wsign-compare] 1056 | for (int j = 1; j <= stan::math::size(y); ++j) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_spatial.h:1529:0: required from ‘stan::promote_args_t::type, T2__, T3__, T4__, typename stan::base_type::type> model_spatial_namespace::lp_distsamp(const std::vector&, const T1__&, const T2__&, const T3__&, const T4__&, const int&, const int&, const T7__&, std::ostream*) [with T1__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2__ = double; T3__ = double; T4__ = double; T7__ = Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_stan_scalar, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T2__, T3__, T4__, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1529 | const auto& conv_const = stan::math::to_ref(conv_const_arg__); stanExports_spatial.h:1613:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_distsamp(const std::vector&, const int&, const T2__&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const int&, const T10__&, std::ostream*) [with T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; T10__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, T7__, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1613 | lp_distsamp( 1614 | stan::model::rvalue(y, "y", 1615 | stan::model::index_min_max( 1616 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1617 | stan::model::index_uni(1)), 1618 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1619 | stan::model::index_uni(2)))), db, 1620 | stan::model::rvalue(log_lambda, "log_lambda", 1621 | stan::model::index_uni(i)), 1622 | stan::model::rvalue(trans_par1, "trans_par1", 1623 | stan::model::index_uni(i)), trans_par2, point, keyfun, 1624 | stan::model::rvalue(conv_const, "conv_const", 1625 | stan::model::index_min_max( 1626 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1627 | stan::model::index_uni(1)), 1628 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1629 | stan::model::index_uni(2)))), pstream__), stanExports_spatial.h:3831:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3831 | get_loglik_distsamp(y, M, aux2, si, lp_state, lp_det, z_dist, 3832 | log_scale, 3833 | stan::model::rvalue(aux1, "aux1", stan::model::index_uni(1)), 3834 | y_dist, aux3, pstream__), "assigning variable log_lik"); stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from ‘Eigen::MapBase::ScalarWithConstIfNotLvalue& Eigen::MapBase::coeffRef(Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long int]’ 15 | EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 367 | matA.col(i).coeffRef(i+1) = 1; | ~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from ‘void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase&, Eigen::DenseBase&, const Eigen::JacobiRotation&) [with VectorX = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]’ 475 | EIGEN_PLAIN_ENUM_MIN(evaluator::Alignment, evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from ‘void Eigen::MatrixBase::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation&) [with OtherScalar = double; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’ 315 | internal::apply_rotation_in_the_plane(x, y, j.transpose()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:895:24: required from ‘void Eigen::internal::tridiagonal_qr_step(RealScalar*, RealScalar*, Index, Index, Scalar*, Index) [with int StorageOrder = 0; RealScalar = double; Scalar = double; Index = long int]’ 895 | q.applyOnTheRight(k,k+1,rot); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:548:87: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 548 | internal::tridiagonal_qr_step(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, -1, 1, false> >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::min_coeff_visitor, -1, 1, false>, 0>; Derived = Eigen::Block, -1, 1, false>]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:323:14: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 323 | this->visit(minVisitor); | ~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:496:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 496 | return minCoeff(index); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:35: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, true>, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:74: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:50: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from ‘Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Block, -1, -1, false>]’ 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:47:25: required from ‘auto stan::math::append_row(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_eigen_t* = 0]’ 47 | result.topRows(Arows) = A.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:3357:0: required from here 3357 | stan::math::append_row(X_state, X_aug), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from ‘auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_spatial.h:924:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of ‘template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > >::val_Op, const Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> > > > > >]’ 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:179:0: required from ‘auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::CwiseUnaryOp, -1, 1>, -1>, void>::apply(const Eigen::VectorBlock, -1, 1>, -1>&)::, const Eigen::Block, -1, 1>, -1, 1, false> >; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 179 | using op_ret_type = plain_type_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 924 | stan::math::subtract(1, stan::math::inv_logit(logit_r)), stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:183:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_spatial.h: In instantiation of ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’: stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) stanExports_spatial.h:1056: warning: comparison of integer expressions of different signedness: ‘int’ and ‘size_t’ {aka ‘long unsigned int’} [-Wsign-compare] 1056 | for (int j = 1; j <= stan::math::size(y); ++j) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from ‘struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false> >’ 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from ‘struct stan::ref_type_if, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&, void>’ 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of ‘template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of ‘template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>&]’ 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_spatial.h:2138:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2138 | const auto& pars1 = stan::math::to_ref(pars1_arg__); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&)::::, const Eigen::ArrayWrapper, -1, 1>, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>, -1, 1, false> > >(Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1>, -1, 1, false> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | = to_ref_if::value>(y_scaled * y_scaled); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from ‘stan::math::var stan::math::accumulator::type>::value, void>::type>::sum() const [with T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value; stan::math::var = stan::math::var_value]’ 135 | inline var sum() const { return stan::math::sum(buf_); } stanExports_spatial.h:3647:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3647 | return lp_accum__.sum(); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, -1>&>(const Eigen::VectorBlock, -1>&):: [with auto:14 = const Eigen::VectorBlock, -1>]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from ‘stan::math::value_of_rec, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:2 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&):: [with auto:14 = const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&>(const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::; Args = {const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:10: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 63 | (2 * as_array_or_scalar(n_double) - 1)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:63:41: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 63 | (2 * as_array_or_scalar(n_double) - 1)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:66:49: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 66 | ntheta = forward_as(signs * theta_val); | ~~~~~~^~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:72:38: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 72 | T_partials_array exp_m_ntheta = exp(-ntheta); | ~~~^~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:53: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ^~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:77:44: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::Array, Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:76:18: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 76 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 77 | (ntheta < -cutoff).select(ntheta, -log1p(exp_m_ntheta)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:41: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~^~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:72: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~^~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper, -1, 1, false> >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:72:62: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 72 | = to_ref_if::value>(inv_logit(-alpha_val)); | ^~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >(const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >&):: [with auto:170 = Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_binary.hpp:231:33: required from ‘stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&):: [with auto:73 = stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; auto:74 = const int; auto:75 = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 231 | return y_inner.unaryExpr( | ~~~~~~~~~~~~~~~~~^ 232 | [f_inner, x_inner](const auto& v) { return f_inner(x_inner, v); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from ‘class stan::math::Holder, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >’ 115 | class Holder | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from ‘auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence, const std::tuple&) [with T = Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; long unsigned int ...Is = {0}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::}; std::index_sequence = std::integer_sequence]’ 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from ‘auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::; long unsigned int ...Is = {0, 1, 2}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > > >(const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const int&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&}; std::index_sequence = std::integer_sequence]’ 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:92:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:94:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ^~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, -1, 1, false> >, void>::apply(const Eigen::ArrayWrapper, -1, 1, false> >&)::, const Eigen::ArrayWrapper, -1, 1, false> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 453 | RealScalar scale = mat.cwiseAbs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:34:74: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:60: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:56: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3557:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3557 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3558 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3559 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:85:34: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3557:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3557 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3558 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3559 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Select, const Eigen::CwiseNullaryOp, Eigen::Array >, const Eigen::Array >, Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Array > >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:83:22: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | = (ntheta > cutoff) | ~~~~~~~~~~~~~~~~~ 83 | .select(-exp_m_ntheta, | ~~~~~~~^~~~~~~~~~~~~~~ 84 | (ntheta >= -cutoff) | ~~~~~~~~~~~~~~~~~~~ 85 | .select(signs * exp_m_ntheta / (exp_m_ntheta + 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 86 | signs)); | ~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3557:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3557 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3558 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3559 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: required from ‘stan::math::var stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix, -1, 1>; stan::require_eigen_st* = 0; stan::require_not_var_matrix_t* = 0; var = var_value]’ 76 | += res.adj() * (arena_v_val.array().val() - res.val()).exp().matrix(); stanExports_spatial.h:954:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_rn(const std::vector&, const T1__&, const T2__&, const int&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 954 | return stan::math::log_sum_exp(lp); stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, 0, Eigen::Stride<0, 0> > > >::val_Op, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_sum_exp.hpp:76:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::Array >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log >(const Eigen::Array&):: [with auto:170 = Eigen::Array]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_column_vector_or_scalar.hpp:60:54: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar > >(Eigen::Transpose >&&):: [with auto:14 = Eigen::Transpose >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv > > >(const Eigen::ArrayWrapper > >&):: [with auto:221 = Eigen::ArrayWrapper > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > > >(const Eigen::ArrayWrapper > >&):: [with auto:170 = Eigen::ArrayWrapper > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:98:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square > > >(const Eigen::ArrayWrapper > >&):: [with auto:239 = Eigen::ArrayWrapper > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp >(const Eigen::Array&):: [with auto:216 = Eigen::Array]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:17: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:27: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp > >, void>::apply(const Eigen::ArrayWrapper > >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs >(const Eigen::Array&):: [with auto:10 = Eigen::Array]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&)::::, const Eigen::ArrayWrapper, 1, -1> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, 1, -1> > > >(Eigen::ArrayWrapper, 1, -1> > >&&):: [with auto:12 = Eigen::ArrayWrapper, 1, -1> > >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv >(const Eigen::Array&):: [with auto:221 = Eigen::Array]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::Array, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square >(const Eigen::Array&):: [with auto:239 = Eigen::Array]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, true>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, true>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, true>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 1, -1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 1, -1, true>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:54: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:75:50: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 75 | (2 / (1 + exp_y_minus_mu_div_sigma) - 1) * inv_sigma); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:36: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ^~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:84:54: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 84 | const auto& exp_mu_div_sigma = to_ref(exp(mu_val * inv_sigma)); | ~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, -1, 1, false> > >(const Eigen::ArrayWrapper, -1, 1, false> >&):: [with auto:170 = Eigen::ArrayWrapper, -1, 1, false> >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper, -1, 1, false> > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_spatial.h:2154:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > > >, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_spatial.h:2165:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:45: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~^~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:58: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~^~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:80:63: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 80 | partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:67: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&):: [with auto:216 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:55: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:35: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:87:12: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:88:11: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 86 | = (1 | ~~ 87 | - 2 * exp_mu_div_sigma / (exp_mu_div_sigma + exp(y_val * inv_sigma))) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | * inv_sigma; | ^~~~~~~~~~~ stanExports_spatial.h:2170:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > >(const Eigen::ArrayWrapper >&):: [with auto:170 = Eigen::ArrayWrapper >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&):: [with auto:10 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:78:67: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | = to_ref_if::value>(abs_diff_y_mu * inv_sigma); | ~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:93:68: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | && !is_constant_all::value)>(diff_sign * inv_sigma); | ~~~~~~~~~~^~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:95:35: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 95 | partials<0>(ops_partials) = -rep_deriv; | ^~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:58: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~~~~^~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:102:43: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | partials<2>(ops_partials) = inv_sigma * (scaled_diff - 1); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/bernoulli_logit_lpmf.hpp:54:16: required from ‘stan::return_type_t stan::math::bernoulli_logit_lpmf(const T_n&, const T_prob&) [with bool propto = false; T_n = std::vector; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 54 | check_not_nan(function, "Logit transformed probability parameter", theta_val); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:827:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_occu(const std::vector&, const T1__&, const T2__&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 827 | stan::math::bernoulli_logit_lpmf(y, logit_p)); stanExports_spatial.h:872:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_occu(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 872 | lp_occu( 873 | stan::model::rvalue(y, "y", 874 | stan::model::index_min_max( 875 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 876 | stan::model::index_uni(1)), 877 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 878 | stan::model::index_uni(2)))), 879 | stan::model::rvalue(logit_psi, "logit_psi", 880 | stan::model::index_uni(i)), 881 | stan::model::rvalue(logit_p, "logit_p", 882 | stan::model::index_min_max( 883 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 884 | stan::model::index_uni(1)), 885 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 886 | stan::model::index_uni(2)))), 887 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 888 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3803:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3803 | get_loglik_occu(y, M, J, si, lp_state, lp_det, 3804 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3805 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:61:15: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 61 | check_finite(function, "Probability parameter", alpha_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = double; T2__ = Eigen::VectorBlock, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix; T5__ = Eigen::Matrix; T7__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3821:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3821 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3822 | log_scale, K, 3823 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3824 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from ‘Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 1, -1, false>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; Eigen::MatrixXd = Eigen::Matrix]’ 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_spatial.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 16, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 16, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 16, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from ‘void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Func = generic_product_impl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]’ 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:333: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 306 | typedef typename Traits::LhsPacket LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:61:15: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = int; T_prob = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 61 | check_finite(function, "Probability parameter", alpha_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:1066:0: required from ‘stan::promote_args_t::type> model_spatial_namespace::lp_pcount_pois(const std::vector&, const T1__&, const T2__&, const int&, const int&, std::ostream*) [with T1__ = stan::math::var_value; T2__ = Eigen::VectorBlock, -1, 1>, -1>; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1066 | stan::math::binomial_logit_lpmf(y, Kmin, logit_p)) + stanExports_spatial.h:1106:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type, T7__>::type, -1, 1> model_spatial_namespace::get_loglik_pcount(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const T7__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; T7__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, T7__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 1106 | lp_pcount_pois( 1107 | stan::model::rvalue(y, "y", 1108 | stan::model::index_min_max( 1109 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1110 | stan::model::index_uni(1)), 1111 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1112 | stan::model::index_uni(2)))), 1113 | stan::model::rvalue(log_lambda, "log_lambda", 1114 | stan::model::index_uni(i)), 1115 | stan::model::rvalue(logit_p, "logit_p", 1116 | stan::model::index_min_max( 1117 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1118 | stan::model::index_uni(1)), 1119 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1120 | stan::model::index_uni(2)))), K, 1121 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1122 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3575:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3575 | get_loglik_pcount(y, M, J, si, lp_state, lp_det, z_dist, 3576 | log_scale, K, 3577 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3578 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 63 | check_finite(function, "Location parameter", mu_val); stanExports_spatial.h:2154:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2154 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_spatial.h:2154:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2154 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > > >(const char*, const char*, const Eigen::ArrayWrapper > >&)::; T = Eigen::ArrayWrapper > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper > >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:83:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_dof = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 83 | check_positive_finite(function, "Degrees of freedom parameter", nu_val); stanExports_spatial.h:2165:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2165 | stan::math::student_t_lpdf(x, pars1, pars2, pars3)); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2175:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1, 1>, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2175 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, 1, -1>; T_scale = Eigen::Matrix, 1, -1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_spatial.h:2154:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Matrix, 1, -1>; T3__ = Eigen::Matrix, 1, -1>; T4__ = Eigen::Matrix, 1, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 2154 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, 1, -1>, void>; Matrix2 = stan::math::arena_matrix, void>; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:23:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:23:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from ‘void stan::math::internal::quad_form_vari_alloc::compute(const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:40:0: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Block, -1, 1, false>]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite, -1, 1, false> > >(const char*, const char*, const Eigen::ArrayWrapper, -1, 1, false> >&)::; T = Eigen::ArrayWrapper, -1, 1, false> >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, -1, 1, false> >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2175:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T2__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T3__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; T4__ = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2175 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, -1, 1, false> > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_spatial.h:2154:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2154 | out = (out + stan::math::normal_lpdf(x, pars1, pars2)); stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/logistic_lpdf.hpp:45:15: required from ‘stan::return_type_t stan::math::logistic_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 45 | check_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2170:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2170 | out = (out + stan::math::logistic_lpdf(x, pars1, pars2)); stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2175:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_single_prior(const T0__&, const int&, const T2__&, const T3__&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex, stan::is_row_vector, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2175 | out = (out + stan::math::gamma_lpdf(x, pars1, pars2)); stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix; T4__ = Eigen::Matrix; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:166:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from ‘static void Eigen::internal::generic_product_impl::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix; LhsT = Eigen::Matrix; RhsT = Eigen::Transpose >; Func = Eigen::internal::assign_op; Scalar = double; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); | ~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp > >(const arena_matrix >&)::; T = stan::math::arena_matrix >]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Array; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Array; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::Array; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1, 1>, -1>; T_loc = int; T_scale = var_value; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 2, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:40: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; Dest = Eigen::Block, -1, 1, false>; typename Dest::Scalar = double]’ 296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; Rhs = Eigen::Transpose >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, 0, Eigen::Stride<0, 0> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:88:38: required from ‘stan::math::log_sum_exp > >(const arena_matrix >&):: [with auto:304 = stan::math::arena_matrix >]’ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:991:0: required from ‘Eigen::Matrix::type, typename stan::base_type::type>::type, -1, 1> model_spatial_namespace::get_loglik_rn(const std::vector&, const int&, const std::vector >&, const std::vector >&, const T4__&, const T5__&, const int&, const std::vector&, std::ostream*) [with T4__ = Eigen::Matrix, -1, 1>; T5__ = Eigen::Matrix, -1, 1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]’ 991 | lp_rn( 992 | stan::model::rvalue(y, "y", 993 | stan::model::index_min_max( 994 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 995 | stan::model::index_uni(1)), 996 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 997 | stan::model::index_uni(2)))), 998 | stan::model::rvalue(log_lambda, "log_lambda", 999 | stan::model::index_uni(i)), 1000 | stan::model::rvalue(logit_p, "logit_p", 1001 | stan::model::index_min_max( 1002 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1003 | stan::model::index_uni(1)), 1004 | stan::model::rvalue(si, "si", stan::model::index_uni(i), 1005 | stan::model::index_uni(2)))), 1006 | stan::model::rvalue(J, "J", stan::model::index_uni(i), 1007 | stan::model::index_uni(1)), K, 1008 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_uni(i)), 1009 | pstream__), "assigning variable out", stan::model::index_uni(i)); stanExports_spatial.h:3566:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3566 | get_loglik_rn(y, M, J, si, lp_state, lp_det, K, 3567 | stan::model::rvalue(Kmin, "Kmin", stan::model::index_omni(), 3568 | stan::model::index_uni(1)), pstream__), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2234:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type> model_spatial_namespace::lp_priors(const T0__&, const std::vector&, const T2__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, 1>; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2234 | lp_single_prior( 2235 | stan::model::rvalue(beta, "beta", stan::model::index_min_max(1, 1)), 2236 | stan::model::rvalue(dist, "dist", stan::model::index_uni(1)), 2237 | stan::model::rvalue(pars, "pars", stan::model::index_uni(1), 2238 | stan::model::index_min_max(1, 1)), 2239 | stan::model::rvalue(pars, "pars", stan::model::index_uni(2), 2240 | stan::model::index_min_max(1, 1)), 2241 | stan::model::rvalue(pars, "pars", stan::model::index_uni(3), 2242 | stan::model::index_min_max(1, 1)), pstream__)); stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2342:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2342 | lp_single_prior(sigma, dist, rep_par1, rep_par2, rep_par3, pstream__)); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/broadcast_array.hpp:32:16: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2347:0: required from ‘stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> model_spatial_namespace::lp_random_prior(const int&, const int&, const T2__&, const std::vector&, const T4__&, const int&, const T6__&, std::ostream*) [with T2__ = Eigen::Matrix, -1, 1>; T4__ = Eigen::Matrix, -1, 1>; T6__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2347 | stan::math::normal_lpdf( 2348 | stan::model::rvalue(b, "b", 2349 | stan::model::index_min_max(idx, 2350 | ((stan::model::rvalue(n_random, "n_random", 2351 | stan::model::index_uni(i)) + idx) - 1))), 0, 2352 | stan::model::rvalue(sigma, "sigma", stan::model::index_uni(i)))); stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:292:8: required from ‘struct Eigen::internal::evaluator > >’ 292 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/csr_matrix_times_vector.hpp:98:16: required from ‘Eigen::Matrix::type, -1, 1> stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix; stan::require_all_not_rev_matrix_t* = 0; typename stan::return_type::type = double]’ 98 | return w_mat * b; | ~~~~~~^~~ stanExports_spatial.h:3776:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3776 | stan::math::csr_matrix_times_vector( 3777 | stan::model::rvalue(Zdim_det, "Zdim_det", 3778 | stan::model::index_uni(1)), 3779 | stan::model::rvalue(Zdim_det, "Zdim_det", 3780 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:31: /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: required from ‘bool boost::range::equal(const SinglePassRange1&, const SinglePassRange2&) [with SinglePassRange1 = boost::iterator_range<__gnu_cxx::__normal_iterator > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/iterator_range_core.hpp:644:32: required from ‘bool boost::operator==(const iterator_range&, const iterator_range&) [with Iterator1T = __gnu_cxx::__normal_iterator >; Iterator2T = __gnu_cxx::__normal_iterator >]’ 644 | return boost::equal( l, r ); | ~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from ‘bool boost::algorithm::split_iterator::equal(const boost::algorithm::split_iterator&) const [with IteratorT = __gnu_cxx::__normal_iterator >]’ 359 | m_Match==Other.m_Match && /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:649:26: required from ‘static bool boost::iterators::iterator_core_access::equal(const Facade1&, const Facade2&, mpl_::true_) [with Facade1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; mpl_::true_ = mpl_::bool_]’ 649 | return f1.equal(f2); | ~~~~~~~~^~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator==(const iterator_facade&, const iterator_facade&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference1 = long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:337: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 62 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 63 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, -1, 1, false> > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3612:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3612 | lp_accum__.add(lp_priors(beta_state, prior_dist_state, 3613 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_spatial.h:2175:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/double_exponential_lpdf.hpp:87:14: required from ‘stan::return_type_t stan::math::double_exponential_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | logp -= sum(scaled_diff); | ~~~^~~~~~~~~~~~~ stanExports_spatial.h:2181:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3624:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3624 | lp_accum__.add(lp_random_prior(has_random_state, n_group_vars_state, 3625 | b_state, n_random_state, sigma_state, 3626 | stan::model::rvalue(prior_dist_state, 3627 | "prior_dist_state", stan::model::index_uni(3)), 3628 | prior_pars_state, pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/quad_form.hpp:59:19: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, false>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:81:75: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 81 | gemm_pack_rhs pack_rhs; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::CopyConstructible::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 167 | BOOST_CONCEPT_USAGE(CopyConstructible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::IncrementableIteratorConcept::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 136 | BOOST_CONCEPT_USAGE(IncrementableIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::EqualityComparable::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 233 | BOOST_CONCEPT_USAGE(EqualityComparable) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:166: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h: In instantiation of ‘Index Eigen::internal::first_default_aligned(const Scalar*, Index) [with Scalar = double; Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’ 89 | Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 500 | return first_aligned::alignment>(array, size); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:169:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheRight(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 169 | this->col(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:304:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 131 | this->row(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 132 | bottom.noalias() -= tau * essential * tmp; | ~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:184:17: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 184 | pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 1; bool ConjugateLhs = false; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 346 | pack_rhs_panel(blockB+j2*actual_kc, | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ 347 | rhs.getSubMapper(actual_k2+panelOffset, actual_j2), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 348 | panelLength, actualPanelWidth, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | actual_kc, panelOffset); | ~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]’ 783 | triangular_product_impl::run(dst, lhs, rhs.nestedExpression(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 2>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 2>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 2>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, 1>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, 1>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, 1>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 5>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, true>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 233 | gemm_pack_rhs pack_rhs_panel; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:42: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:57: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:73:50: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Transpose, -1, -1, false>, 1, -1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; ExpressionType = Eigen::Block, -1, -1, false>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 319 | pack_lhs_panel(blockA, lhs.getSubMapper(i2,absolute_j2), | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 320 | actualPanelWidth, actual_mc, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 321 | actual_kc, j2); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 150 | Matrix triangularBuffer(a); | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 153 | triangularBuffer.diagonal().setZero(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from ‘ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]’ 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:444:18: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:336:80: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > > >’ 336 | typedef typename DenseCoeffsBase::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:282:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >’ 282 | struct evaluator, Options, StrideType> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseUtil.h:121:8: required from ‘struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 121 | struct plain_object_eval | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseDenseProduct.h:187:104: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; int ProductType = 7; Scalar = double]’ 187 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Derived = Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::SparseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from ‘auto stan::math::csr_matrix_times_vector(int, int, const T1&, const std::vector&, const std::vector&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_any_rev_matrix_t* = 0]’ 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); stanExports_spatial.h:3530:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3530 | stan::math::csr_matrix_times_vector( 3531 | stan::model::rvalue(Zdim_det, "Zdim_det", 3532 | stan::model::index_uni(1)), 3533 | stan::model::rvalue(Zdim_det, "Zdim_det", 3534 | stan::model::index_uni(2)), Zw_det, Zv_det, Zu_det, b_det)), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from ‘void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, Eigen::Transpose >, 1> >; Functor = Eigen::internal::assign_op; int Version = 1; Eigen::Index = long int]’ 654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col)); | ~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Derived = Eigen::Block, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from ‘Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, false>; Scalar = double]’ 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::OuterStride<> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:39:18: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:57: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:42: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:301:29: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/access_helpers.hpp:92:0: required from ‘void stan::model::internal::assign_impl(T1&&, T2&&, const char*) [with T1 = Eigen::Matrix&; T2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; stan::require_all_eigen_t* = 0]’ 92 | x = std::forward(y); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from ‘void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]’ 60 | internal::assign_impl(x, std::forward(y), name); stanExports_spatial.h:3768:0: required from ‘void model_spatial_namespace::model_spatial::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 3768 | stan::model::assign(lp_state, 3769 | stan::math::add(stan::model::deep_copy(lp_state), 3770 | stan::math::multiply(Kmat, b_state)), "assigning variable lp_state"); stanExports_spatial.h:4353:0: required from ‘void model_spatial_namespace::model_spatial::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 4353 | write_array_impl(base_rng, params_r, params_i, vars, 4354 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_spatial.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here 34 | return crossprod(B * llt_of_S.matrixU()); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block, -1, -1, false>; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; int Side = 1; int Mode = 2]’ 71 | triangular_solve_vector | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:32: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]’ 194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, 1, false>]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_spatial_namespace::model_spatial; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_spatial.h:3515:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3515 | stan::math::add(stan::math::multiply(X_state_all, beta_state), stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 341 | dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false> >, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false> >, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::InnerStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::InnerStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::InnerStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:106: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block, -1, -1, false>, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 327 | internal::triangular_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 328 | | ~~~~~~~~~ 332 | ::run(actualLhs.rows(),actualLhs.cols(), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 333 | actualLhs.data(),actualLhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 334 | actualRhsPtr,1, | ~~~~~~~~~~~~~~~ 335 | dest.data(),dest.innerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 336 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:27: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_spatial_namespace::model_spatial; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_spatial.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 27 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 27 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 31 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 31 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_spatial.h:2384:0: required from ‘stan::promote_args_t::type, T1__, typename stan::base_type::type> model_spatial_namespace::theta_lpdf(const T0__&, const T1__&, const T2__&, const int&, std::ostream*) [with bool propto__ = true; T0__ = Eigen::Matrix, -1, 1>; T1__ = stan::math::var_value; T2__ = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, T1__, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = double; std::ostream = std::basic_ostream]’ 2384 | stan::math::quad_form(Qalpha, theta)))); stanExports_spatial.h:3638:0: required from ‘stan::scalar_type_t model_spatial_namespace::model_spatial::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 3638 | lp_accum__.add(theta_lpdf(b_state, tau, Qalpha, n_eigen, 3639 | pstream__)); stanExports_spatial.h:4364:0: required from ‘T_ model_spatial_namespace::model_spatial::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 4364 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_spatial_namespace::model_spatial; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_spatial_namespace::model_spatial; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_spatial.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::sum > >(const std::vector, arena_allocator > >&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, 1, 1, 0, 1, 1> >::adj_Op, Eigen::Matrix, 1, 1, 0, 1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:89:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 89 | matrix_d adjC = impl_->C_.adj(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>&>(Eigen::Matrix, -1, 1>&):: [with auto:12 = Eigen::Matrix, -1, 1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(Eigen::Matrix, -1, 1>&)::; Args = {Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from ‘auto stan::math::value_of(EigMat&&) [with EigMat = Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]’ 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = Eigen::Map >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:22:9: required from ‘class Eigen::internal::SparseTransposeImpl, 0, Eigen::Stride<0, 0> >, 1024>’ 22 | class SparseTransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseTranspose.h:45:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Sparse>’ 45 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: recursively required from ‘void stan::math::internal::csr_adjoint::chain() [with Result_ = stan::math::arena_matrix, -1, 1> >&; WMat_ = stan::math::var_value >&; B_ = stan::math::arena_matrix, -1, 1> >&]’ 27 | void chain() { chain_internal(res_, w_mat_, b_); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:27:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 4>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 4>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 4>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:402:50: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, Eigen::Matrix, 1, 4>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0>, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:409:50: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:618:37: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:618:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index) const [with Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; int ProductTag = 4; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 618 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:660:61: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:618:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index) const [with Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int ProductTag = 4; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long int]’ 618 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:660:61: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block >, 1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, 1, false> >, const Eigen::Block, 1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_spatial_namespace::model_spatial; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 27 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from ‘void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from ‘void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 78 | chainB(B, Ad, Bd, adjC); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from ‘void stan::math::internal::quad_form_vari::chain() [with Ta = double; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = 1]’ 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ g++ -std=gnu++17 -shared -L/usr/lib64/R/lib -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -o ubms.so RcppExports.o exp_counts_occu.o loglik.o simz.o stanExports_colext.o stanExports_single_season.o stanExports_spatial.o -L/usr/lib64 -Wl,-rpath,/usr/lib64 -ltbb -ltbbmalloc -L/usr/local/lib/R/library/RcppParallel/lib/ -Wl,-rpath,/usr/local/lib/R/library/RcppParallel/lib/ -ltbb -ltbbmalloc -lflexiblas -lgfortran -lm -lquadmath -L/usr/lib64/R/lib -lR installing to /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT/usr/local/lib/R/library/00LOCK-ubms/00new/ubms/libs ** R ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices converting help for package ‘ubms’ finding HTML links ... done RSR html coef-ubmsFit-method html extract-ubmsFit-method html extract_log_lik html fitList-ubmsFit-method html fitted-ubmsFit-method html getY-ubmsFit-method html get_elapsed_time-ubmsFit-method html get_stancode-ubmsFit-method html gof html kfold-ubmsFit-method html loo-ubmsFit-method html modSel-ubmsFitList-method html names-ubmsFit-method html names-ubmsFitList-method html nsamples-ubmsFit-method html plot-ubmsFit-ANY-method html plot_effects-ubmsFit-method html plot_posteriors-ubmsFit-method html plot_residuals-ubmsFit-method html plot_spatial html posterior_linpred-ubmsFit-method html posterior_predict-ubmsFit-method html predict-ubmsFit-method html priors html projected html ranef-ubmsFit-method html residuals-ubmsFit-method html stan_colext html stan_distsamp html stan_multinomPois html stan_occu html stan_occuRN html stan_occuTTD html stan_pcount html sub-ubmsFit-character-missing-missing-method html sub-ubmsSubmodelList-character-missing-missing-method html summary-ubmsFit-method html traceplot-ubmsFit-method html turnover html ubms html ubmsFitList-extractors html waic-ubmsFit-method html ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** checking absolute paths in shared objects and dynamic libraries ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (ubms) + test -d ubms/src + cd ubms/src + rm -f RcppExports.o exp_counts_occu.o loglik.o simz.o stanExports_colext.o stanExports_single_season.o stanExports_spatial.o ubms.so + rm -f /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT/usr/local/lib/R/library/R.css + find /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT/usr/local/lib/R/library -type f -exec sed -i s@/builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT@@g '{}' ';' + /usr/bin/find-debuginfo -j4 --strict-build-id -m -i --build-id-seed 1.2.7-1.fc42.copr8100729 --unique-debug-suffix -1.2.7-1.fc42.copr8100729.x86_64 --unique-debug-src-base R-CRAN-ubms-1.2.7-1.fc42.copr8100729.x86_64 --run-dwz --dwz-low-mem-die-limit 10000000 --dwz-max-die-limit 110000000 -S debugsourcefiles.list /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/ubms find-debuginfo: starting Extracting debug info from 1 files DWARF-compressing 1 files sepdebugcrcfix: Updated 1 CRC32s, 0 CRC32s did match. Creating .debug symlinks for symlinks to ELF files Copying sources found by 'debugedit -l' to /usr/src/debug/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.x86_64 1206 blocks find-debuginfo: done + /usr/lib/rpm/check-buildroot + /usr/lib/rpm/redhat/brp-ldconfig + /usr/lib/rpm/brp-compress + /usr/lib/rpm/redhat/brp-strip-lto /usr/bin/strip + /usr/lib/rpm/brp-strip-static-archive /usr/bin/strip + /usr/lib/rpm/redhat/brp-mangle-shebangs + /usr/lib/rpm/brp-remove-la-files + env /usr/lib/rpm/redhat/brp-python-bytecompile '' 1 0 -j4 + /usr/lib/rpm/redhat/brp-python-hardlink + /usr/bin/add-determinism --brp -j4 /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT Scanned 30 directories and 203 files, processed 148 inodes, 0 modified (0 replaced + 0 rewritten), 0 unsupported format, 0 errors Reading /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/SPECPARTS/rpm-debuginfo.specpart Processing files: R-CRAN-ubms-1.2.7-1.fc42.copr8100729.x86_64 Provides: R-CRAN-ubms = 1.2.7-1.fc42.copr8100729 R-CRAN-ubms(x86-64) = 1.2.7-1.fc42.copr8100729 Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Requires: libR.so()(64bit) libc.so.6()(64bit) libc.so.6(GLIBC_2.11)(64bit) libc.so.6(GLIBC_2.14)(64bit) libc.so.6(GLIBC_2.2.5)(64bit) libc.so.6(GLIBC_2.3.4)(64bit) libc.so.6(GLIBC_2.38)(64bit) libc.so.6(GLIBC_2.4)(64bit) libc.so.6(GLIBC_ABI_DT_RELR)(64bit) libflexiblas.so.3()(64bit) libgcc_s.so.1()(64bit) libgcc_s.so.1(GCC_3.0)(64bit) libgcc_s.so.1(GCC_3.3.1)(64bit) libm.so.6()(64bit) libm.so.6(GLIBC_2.2.5)(64bit) libm.so.6(GLIBC_2.23)(64bit) libm.so.6(GLIBC_2.29)(64bit) libstdc++.so.6()(64bit) libstdc++.so.6(CXXABI_1.3)(64bit) libstdc++.so.6(CXXABI_1.3.15)(64bit) libstdc++.so.6(CXXABI_1.3.5)(64bit) libstdc++.so.6(CXXABI_1.3.9)(64bit) libstdc++.so.6(GLIBCXX_3.4)(64bit) libstdc++.so.6(GLIBCXX_3.4.11)(64bit) libstdc++.so.6(GLIBCXX_3.4.15)(64bit) libstdc++.so.6(GLIBCXX_3.4.18)(64bit) libstdc++.so.6(GLIBCXX_3.4.19)(64bit) libstdc++.so.6(GLIBCXX_3.4.20)(64bit) libstdc++.so.6(GLIBCXX_3.4.21)(64bit) libstdc++.so.6(GLIBCXX_3.4.26)(64bit) libstdc++.so.6(GLIBCXX_3.4.29)(64bit) libstdc++.so.6(GLIBCXX_3.4.30)(64bit) libstdc++.so.6(GLIBCXX_3.4.32)(64bit) libstdc++.so.6(GLIBCXX_3.4.9)(64bit) libtbb.so.12()(64bit) rtld(GNU_HASH) Processing files: R-CRAN-ubms-debugsource-1.2.7-1.fc42.copr8100729.x86_64 Provides: R-CRAN-ubms-debugsource = 1.2.7-1.fc42.copr8100729 R-CRAN-ubms-debugsource(x86-64) = 1.2.7-1.fc42.copr8100729 Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Processing files: R-CRAN-ubms-debuginfo-1.2.7-1.fc42.copr8100729.x86_64 Provides: R-CRAN-ubms-debuginfo = 1.2.7-1.fc42.copr8100729 R-CRAN-ubms-debuginfo(x86-64) = 1.2.7-1.fc42.copr8100729 debuginfo(build-id) = f565a16d869e9ee6e211d0d6536ca1fe5989e9c8 Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Recommends: R-CRAN-ubms-debugsource(x86-64) = 1.2.7-1.fc42.copr8100729 Checking for unpackaged file(s): /usr/lib/rpm/check-files /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build/BUILDROOT Wrote: /builddir/build/RPMS/R-CRAN-ubms-debugsource-1.2.7-1.fc42.copr8100729.x86_64.rpm Wrote: /builddir/build/RPMS/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.x86_64.rpm Wrote: /builddir/build/RPMS/R-CRAN-ubms-debuginfo-1.2.7-1.fc42.copr8100729.x86_64.rpm Executing(rmbuild): /bin/sh -e /var/tmp/rpm-tmp.6HS7H8 + umask 022 + cd /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + test -d /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + rm -rf /builddir/build/BUILD/R-CRAN-ubms-1.2.7-build + RPM_EC=0 ++ jobs -p + exit 0 RPM build warnings: %source_date_epoch_from_changelog is set, but %changelog has no entries to take a date from Finish: rpmbuild R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm Finish: build phase for R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-rawhide-x86_64-1727860992.197419/root/var/log/dnf5.log INFO: Done(/var/lib/copr-rpmbuild/results/R-CRAN-ubms-1.2.7-1.fc42.copr8100729.src.rpm) Config(child) 7 minutes 58 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_success=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot Finish: run Running RPMResults tool Package info: { "packages": [ { "name": "R-CRAN-ubms-debuginfo", "epoch": null, "version": "1.2.7", "release": "1.fc42.copr8100729", "arch": "x86_64" }, { "name": "R-CRAN-ubms", "epoch": null, "version": "1.2.7", "release": "1.fc42.copr8100729", "arch": "src" }, { "name": "R-CRAN-ubms", "epoch": null, "version": "1.2.7", "release": "1.fc42.copr8100729", "arch": "x86_64" }, { "name": "R-CRAN-ubms-debugsource", "epoch": null, "version": "1.2.7", "release": "1.fc42.copr8100729", "arch": "x86_64" } ] } RPMResults finished